High-Throughput Approaches

9.24

High-Throughput Approaches

AJ Vegas and DG Anderson, Massachusetts Institute of Technology, Cambridge, MA, USA © 2012 Elsevier B.V. All rights reserved.

9.24.1 9.24.2 9.24.3 9.24.3.1 9.24.3.2 9.24.3.3 9.24.4 9.24.5 9.24.6 9.24.6.1 9.24.6.2 9.24.6.3 9.24.7 9.24.8 9.24.9 References

Introduction Polyarylates Cationic Polymers Poly(β-amino esters) PEI-Derived Polymers Lipidoids Organic Coatings Polyolefin Catalyst Discovery Polymers Generated through Radical Polymerization Atom-Transfer Radical Polymerization Reversible Addition-Fragmentation Chain Transfer Nitroxide-Mediated Polymerization Ring-Opening Polymerizations Microarray Approaches Other High-Throughput Screening Approaches

9.24.1 Introduction The myriad of industrial, commercial, and medicinal applica­ tions of polymeric materials makes their discovery and development a constant and fundamental need in a variety of fields. In general, the large number of potential parameters in polymer synthesis, characterization, and evaluation make the application of high-throughput combinatorial methods one useful approach for this avenue of research. Laboratory automation previously feasible for only large companies has now become accessible to academic research groups, greatly enhancing efforts to apply combinatorial methods.1–3 The application of high-throughput methods is now growing rapidly and the progress reviewed here will already be outdated by the time of publication of this chapter. Here we provide an overview of the area as it applies to medicinal, commercial, and industrial applications. The application of combinatorial methods has been more widely practiced in the development of small-molecule collections than polymers, with the notable exception of peptides.1,2,4–6 In the small-molecule context, combinatorial approaches center around structural variation of the products, and the structure–function relationships that can be observed. However, there are additional parameters when constructing polymers that greatly influence the resulting properties, and systematic variation of these parameters through combinatorial investigation establishes relationships with emergent proper­ ties. Molecular weight (MW), polydispersity, and processing/ formulation are a few parameters that are common to all polymers that can be determined in the final properties of the material. In addition, the structure–property and parameter– property relationships that are established by evaluating a combinatorial collection of polymers can provide insights and lead to new hypotheses about designing new generations of materials. The synthesis, characterization, and evaluation of multiple combinations surrounding a certain polymeric framework Polymer Science: A Comprehensive Reference, Volume 9

457 458 460 460 462 463 466 469 471 471 472 474 476 478 479 482

place demands on throughput and speed of execution. While skilled researchers may be able to synthesize a respectable number of macromolecules in a reasonable time frame, the repetitive and laborious nature of this work makes it ideal for robotic automation. Over the years, a number of companies have developed automation to address high-throughput poly­ mer synthesis, formulation, and characterization. A number of reviews have described the various automation platforms that are available,1–7 with Chemspeed and Symyx emerging as the most widely utilized platforms in the field (Figure 1). Robotic platforms from both of these companies are cited in the major­ ity of the publications surrounding high-throughput polymer experimentation, and the demand for these platforms will likely grow with the field. Common to all synthesis automation is liquid handling, mixing, heating/cooling, weighing, solid dispensing, and the ability to function in an inert environment. Liquid handling on these platforms is often tolerant of a wide range of viscosities, whether aqueous or organic, and may also provide solutions for parallel liquid transfer or even heated liquid transfer. Mixing encompasses four distinct forms of agi­ tation including rotary and tumbling (both require magnetic stir bars), vortexing, and overhead stirring. Some of these auto­ mation systems now handle a variety of different glassware formats such as commercially available vials that eliminate the need for custom glassware. In addition, the software packages that have been developed to either plan experiments or execute a synthesis have become increasingly graphically interfaced and user-friendly, making it simple for a researcher to plan and complete their experiments.1,3,7 While advances in automation have increased the throughput of polymer synthesis, macromolecular characteri­ zation remains a significant bottleneck in high-throughput approaches. Typical characterization methods such as matrix-assisted laser desorption/ionization (MALDI) spectro­ metry and nuclear magnetic resonance (NMR) spectroscopy are not yet amenable to high-throughput analysis, while Fourier transform infrared (FTIR) spectroscopy is now available

doi:10.1016/B978-0-444-53349-4.00231-4

457

458

High-Throughput Approaches

(a)

(b)

Figure 1 Commercial automation platforms for high-throughput synthesis and formulation. (a) The Symyx core module (CM) synthesis platform. (b) The Chemspeed Swing SLT platform. Images reproduced with permission from Freeslate Inc. and Chemspeed Technologies, respectively.

with considerable throughput. Gel-permeation chromatogra­ phy (GPC) with the advent of flow-injection analysis has achieved respectable levels of throughput, with analysis times of about 30–45 min being reduced to 5–10 min by sacrificing information about sample purity. Differential scanning calori­ metry (DSC) and thermal gravimetric analysis (TGA) instrumentation with modest throughput are available for determining polymer properties. Some newly developed approaches to high-throughput surface characterization via instron analysis, time-of-flight secondary ion mass spectrome­ try (ToF-SIMS), imaging, and X-ray photoelectron spectroscopy (XPS) on high-throughput platforms are reviewed here. Methods to evaluate polymer collections vary widely and in many cases are unique to select for the desired properties of a given application. These methods tend to have a good through­ put and can often be performed prior to characterization to avoid a bottleneck in screening workflow. For all of the selected examples described forthwith, high-throughput workflows were tailored to the specific aims and goals of each research endeavor. However, the combinatorial approach employed always uses systematic variation to understand measured outcomes.

9.24.2 Polyarylates Amino acid-based polymers have been investigated as a poten­ tial source of valuable biomaterials for several decades.8,9 However, with the notable exception of poly(γ-substituted glu­ tamates), most amino acid-derived polymers exhibit problems with immunogenicity and poor mechanical properties for most biomedical applications. In order to overcome these limita­ tions, Bourke and Kohn8–11 devised a combinatorial strategy using amino acid monomers polymerized through non-amide

bonds, known as pseudo-poly(amino acids). The systematic structural variations employed by this approach allowed the researchers to draw important correlations between material properties and biological outcomes. Since aromatic features in polymeric backbones correlate with increased mechanical stability and stiffness, researchers chose to focus on tyrosine-derived polymers.10–12 After several investigations into potential tyrosine-derived structures that would lead to biodegradable and useful polymers, investiga­ tors discovered desaminotyrosyl-tyrosine alkyl esters (DTRs) as valuable monomers for pseudo-poly(amino acids). A combi­ natorial library of 112 polyarylates was synthesized by reacting 14 tyrosine-derived diphenols and 8 diacids using 1,3-diiso­ propylcarbodiimide as a coupling agent (Figure 2).10,11 These reactions were performed in parallel without the use of auto­ mation, although the authors state that their methodology is easily adaptable for an automated workflow. Characterization of the polymer collection revealed MWs ranging from 50 000 to 150 000 Da, with polydispersity indexes (PDIs) ranging from 1.4 to 2.0.9,11,13 This collection represented the first published combinatorial library of degradable materials.8,10–15 Analysis of the library revealed a glass transition tempera­ ture range of 2–91 °C and water contact angles (WCAs) of 64–101°.8,10,11 These values changed incrementally and corre­ lated with small changes in polymeric structure, allowing for interesting structure–property correlations to be established: (1) glass transition temperature and contact angle decreased with smaller number of methylene groups in the polymers; (2) methylene substitution of the diacid monomer impacted the transition temperature more than the diphenol monomer; (3) alkyl branching increased transition temperature but not contact angle; and (4) increased oxygen substitution lowered the contact angle.8,10,11 The maximum tensile strength of these polymers was determined to lie in a range from 45 MPa to

Figure 2 Synthesis of tyrosine-derived polyarylates. DIPC, 1,3-diisopropylcarbodiimide; DMAP, dimethylaminopyridine; PTSA, p-toluenesulfonic acid.

High-Throughput Approaches

Fibrinogen adsor ption (% of control)

1.7 GPa, and a higher number of methylene groups in the polymer correlated with softer materials. Researchers then took 42 representative polymers from this library and mea­ sured in vitro cellular proliferation with a rat lung fibroblast cell line in an effort to establish correlations between polymer properties and biological outcomes.8,9,11 WCAs correlated well with cell proliferation, with polymers derived from oxygen-containing diacid monomers proving to be the best substrates. Overall, a WCA of 70° over a wide range of glass transition temperatures was deemed optimal for cell growth and proliferation. Looking to establish structure–property relationships in a different biological context, Kohn et al.12 and Effah-Kaufmann and Kohn15 also examined the impact of their polyarylate library on the proliferation of UMR-106 osteoblast-like cells and fibrinogen adsorption as a measure of polymer biocom­ patibility. An analysis of total DNA concentration as well as metabolic and alkaline phosphatase activity after exposure of UMR-106 osteoblast-like cells to polyarylates revealed no noticeable cytotoxicity, with alkaline phosphatase and meta­ bolic activities equivalent to that observed with tissue culture polystyrene. Polymers containing short ethyl ester side chains stimulated cell proliferation more effectively than more hydro­ phobic ester side chains, while no correlations were observed between cell growth and structural features of the polymer backbone. Due to the important role of adhesion of plasma proteins in determining blood compatibility and the key role of fibrinogen in these processes, investigators developed an in vitro assay to test fibrinogen adsorption to polymer surfaces.8,9,14 Casting of 46 different polymers (44 polyarylates, poly(lactic

459

acid) (PLA), and poly(lactide-co-glycolide) (PLGA)) into a 384­ well microplate format with an immunofluorescence-based detection scheme allowed for fast evaluation of protein adsorp­ tion (Figure 3). Polymer-casted wells were treated with human fibrinogen and blocked with bovine serum albumin (BSA, to minimize nonspecific binding) prior to treatment with fluor­ escein-labeled anti-fibrinogen IgG polyclonal antibody.9,14 Measurement of fluorescent levels using a standard fluores­ cent plate reader correlated with protein adsorption on the polymer surface. Polymer composition clearly demonstrated an effect on fibrinogen adsorption. Greater WCAs roughly led to reduced adsorption overall, but structural differences between the polymers had a greater impact on protein association (Figure 4). For example, despite similar WCA and physicome­ chanical properties, poly(DTR diglycolate)s exhibited significantly higher fibrinogen adsorption than the correspond­ ing poly(DTR glutarate)s.9,14 This result suggests that even minor structural differences that have little impact on overall physical properties can drastically impact protein adsorption. The extensive characterization of this polymer collection has enabled the development of mathematical models to help pre­ dict structure–activity relationships and aid in polymer selection with specific physical and biological properties for biomedical applications.9,16,17 In a study by Yang et al.,16 researchers selected two polyarylates, pDTEc (poly(desaminotyrosyl-tyrosine ethyl ester carbonate)) and pDTOc (poly(desaminotyrosyl-tyrosine octyl ester carbonate)), to make three-dimensional (3D) combinatorial library scaffolds that can aid in understanding cell–biomaterial interactions by providing a more physiologi­ cally relevant environment and developing more effective tissue-engineered devices. These two polymers share a

300 250

200 150

100

50 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 1. p(DTiB sebacate)

13. p(DTH glutarate)

25. p(DTO succinate)

37. p(DTiP 3-methyl adipate)

2. p(HTH sebacate)

14. p(DTiB adipate)

26. p(DTB succinate)

38. p(DTB adipate)

3. p(DTO glutarate)

15. p(DTM sebacate)

27. p(DTB glutarate)

39. p(DTB 3-methyl adipate)

4. p(DTH adipate)

16. p(DTsB suberate)

28. p(DTB suberate)

40. p(DTH diglycolate)

5. p(DTO sebacate)

17. p(DTBn suberate)

29. p(DTBn adipate)

41. p(DTE 3-methyl adipate)

6. p(HTH suberate)

18. p(HTE suberate)

30. p(HTE 3-methyl adipate)

42. p(DTE glutarate)

7. p(DTO adipate)

19. p(DTsB adipate)

31. p(DTE adipate)

43. p(lactic glycolic acid)

8. p(DTO suberate)

20. p(HTE adipate)

32. p(DTM adipate)

44. p(lactic acid)

9. p(HTH adipate)

21. p(DTM 3-methyl adipate)

33. p(DTsB 3-methyl adipate)

45. p(HTE succinate)

10. p(DTBn sebacate)

22. p(DTH succinate)

34. p(DTO diglycolate)

46. p(DTB diglycolate)

11. p(DTH 3-methyl adipate)

23. p(DTB suberate)

35. p(DTsB 3-methyl adipate)

12. p(DTH suberate)

24. p(DTiP adipate)

36. p(DTBn 3-methyl adipate)

Figure 3 Fibrinogen absorption of 46 different polyarylates. Reprinted from Weber, N; Bolikal, D.; Bourke, S. L; Kohn, J. J. Biomed. Mater. Res., Part A 2004, 68A (3), 496–503,14 with permission from Wiley.

High-Throughput Approaches

(b)

Adipates

R2 = 0.43

90 85

Fibrinogen adsorption (% of control)

95

200

R2 = 0.73

150 100 50 0 65

80

70

75

80

85

75 70

R2 = 0.87

200 150 100

R2 = 0.98

50 0

90

65

65 60 0

100 200 300 Fibrinogen adsorption (% of control)

200

2 R = 0.87

150 100 50 0 65

70

75

80

85

70

75

80

85

90

Contact angle (deg)

Suberates

250

Glutarates

250

Contact angle (deg)

Fibrinogen adsorption (% of control)

Air−water contact angle

100

Diglycolates

250

Fibrinogen adsorption (% of control)

(a)

Fibrinogen adsorption (% of control)

460

3-Methyl adipates

250 200

R2 = 0.67

150 100 50 0

90

Contact angle (deg)

65

70

75

80

85

90

Contact angle (deg)

Figure 4 Relationship of polyarylate air–water contact angle with fibrinogen adsorption. (a) No overall correlation exists over all 46 tested polyarylates. (b) Examination by polymer substructure reveals correlations that are structure-dependent. Reprinted from Weber, N.; Bolikal, D.; Bourke, S. L.; Kohn, J. J. Biomed. Mater. Res., Part A 2004, 68A (3), 496–503,14 with permission from Wiley.

structurally identical backbone, but possess different side chains, which impart different WCAs, glass transition tempera­ tures, mechanical properties, and degradation rates. An enhancement of cell spreading, adhesion, and proliferation was observed for pDTEc over pDTOc, in addition to differential gene expression in osteoblast and macrophage cell lines. Implementing a combinatorial polymer blend approach between these two polymers was seen as a good test system to reveal differences in cellular behavior. A syringe-pump system blended the two polymer solutions in various continuous ratios into a 96-well microplate allowing researchers to gener­ ate 14 combinatorial libraries reflecting 36 different polymer compositions and 12 controls.16 Freeze-drying and water leach­ ing of sodium chloride in the wells generated large, macroporous (200–400 µm pore size) scaffolds. FTIR spectro­ scopy and scanning electron microscopy (SEM) were used to verify both polymer blend composition and scaffold morphol­ ogy. MC3T3-E1 osteoblast cells were incubated with scaffolds for 1 day and then analyzed for adhesion, morphology, pene­ tration, and proliferation. Cell culturing in 3D scaffolds showed good agreement with 2D film approaches. In a separate report, Yang et al.17 expanded this approach to identify optimal tissue scaffolds for X-ray imaging (Figure 5). As the first described degradable combinatorial library of materials, polyarylates generated a blueprint for the character­ ization and evaluation of polymer libraries. The presence of common structural features in this combinatorial library along with its extensive characterization facilitated correlation with biological outcomes that influence polymer selection for bio­ medical applications.8,9

9.24.3 Cationic Polymers The rising interest in nucleic acid therapy has led to increased attention on cationic polymers as effective delivery agents. Although much progress has been made, significant challenges

remain, and to date there are still no FDA-approved gene therapy or small interfering RNA (siRNA) therapy treatments. Poly(ethyleneimine) (PEI) is a cationic polymer that has received considerable attention due to its high transfection efficiency in vitro, but the polymer causes considerable systemic toxicity. A number of combinatorial approaches have been taken to develop new cationic polymers that may serve as more efficient transfection agents with low toxicities.

9.24.3.1

Poly(β-amino esters)

A Michael addition reaction between unsaturated esters and amines has been utilized to generate a new class of cationic polymers, known as poly(β-amino esters) (PBAEs) (Figure 6).18 Initial studies evaluated the potential of these materials to overcome cellular barriers to gene transfer and characterized the polyplexes by measuring the zeta potential and effective diameter.19 Subsequent high-throughput expan­ sion of these studies created a library of 2350 cationic polymers in a semiautomated fashion.20 Utilizing fluid-handling robotics and multichannel pipettors, 25 bis-acrylate esters and 94 primary/secondary amines were diluted in dimethyl sulfox­ ide (DMSO), combined in a microplate format, and heated for several days.20 This format allowed for the entire collection to be screened for cytotoxicity and transfection efficiency. Polymers were formulated at three different DNA (encoding luciferase) to polymer ratios and formulations that displayed comparable or improved levels of luminescence to PEI were also examined for DNA complexation in a gel-shift binding assay. The top 93 best-performing polymers from the initial screen were also optimized for transfection efficiency by refin­ ing their DNA/polymer ratios. Forty-six polymers were identified that transfect better than PEI and all but two of these polymers displayed DNA-binding ability. As an addi­ tional test of transfection potential, the top 10 performers were evaluated for delivery of a green fluorescent protein

High-Throughput Approaches

(b)

pDTEc

pl2DTEc

O O

O

HN

O O

HN

O

O

O O

O

O O

(radiolucent)

(radiopaque, due to covalently

linked iodine atoms)

pDTEc

Static

mixer

Expanded view of static mixer

Polymer solutions are deposited

into trough containing

sieved NaCl while a

motorized stage

moves trough

during polymer

deposition

Gradient librar y #2

pl2DTEc

Gradient librar y #1

Syringe pumps

pl2DTEc control

(d)

(c)

pDTEc control

(a)

461

Figure 5 Iodine-enriched polyarylate gradient scaffolds for improved X-ray imaging. (a, b) Structures of the two polyarylates used to make the gradient library. (c) Deposition and mixing of the two polymers results in polymer scaffolds with varying composition. (d) Representative scaffold libraries. Reprinted from Yang, Y. Y.; Dorsey, S. M.; Becker, M. L.; et al. Biomaterials 2008, 29 (12), 1901–1911,17 with permission from Elsevier.

Figure 6 Synthesis of PBAEs by a Michael addition reaction.

plasmid, pCMV-eGFP, into COS-7 cells. High levels of transfec­ tion were observed for all 10 of the polymers tested.20 The hits identified from these screens also displayed inter­ esting structure–activity relationships. Almost all of the top performers had a hydrophobic diacrylate monomer, and among the most effective polymers amino dialcohol and bis(secondary amines) monomers were well represented.20 In vivo evaluation of the best-performing polymer, labeled C32, was compared to PEI for toxicity and DNA delivery in a mouse xenograft tumor model with human prostate cancer cells.21 C32 transfected a luciferase DNA plasmid fourfold better than PEI and 26-fold more efficiently than the naked

DNA in intratumoral injections. Intramuscular injections resulted in lower transfection efficiency for C32 than either PEI or naked DNA. No toxicity was observed with C32 in these injections while PEI displayed considerable toxicity. Researchers went on to show that C32 can deliver a gene encoding diphtheria toxin to the same mouse xenograft pros­ trate cancer model and observed that 40% of the tested tumors regressed.21 A second-generation library of 486 PBAEs was generated to examine the structure–function relationships with greater reso­ lution.22 High-throughput screening of luciferase DNA transfection in COS-7 cells followed by biophysical

462

High-Throughput Approaches and cellular DNA uptake was measured (Figure 7). Two end-modified C32 polymers were identified with a higher DNA affinity and formed smaller nanoparticles with DNA than the regular amino alcohol-terminated C32. Conversely, diacrylate-terminated polymers were demonstrated to undergo UV-induced photo-cross-linking of the polymer chains to give an array of degradation and mechanical properties.26 These results highlight not only the new materials that can be dis­ covered using a high-throughput combinatorial approach, but also the predictive relationships that can be established.

characterization of top-performing polyplexes revealed dia­ meters smaller than 150 nm and positive ζ potentials in buffer. The top polymers also had MWs greater than 10 000 Da and the best nine polymers structurally converged around amino alcohol monomers combined with hydropho­ bic diacrylate monomers. Of these nine polymers, the top three differed by only one carbon atom. Since all initial screens were performed under serum-free conditions, researchers examined the impact of serum on the efficacy of these polymer formula­ tions.22,23 Particle size increased under these conditions, with the top formulations increasing to 200 nm but other formula­ tions forming micrometer-sized aggregates. The ζ potentials of particles in serum were negative, as opposed to positive in buffer, presumably due to the absorption of negatively charged serum proteins to the surface of the polyplexes. Changes in structure correlated well with these changes in particle size and ζ potential, and the serum-determined properties of these formulations were predictive of DNA transfection of human umbilical vein endothelial cells (HUVECs) in serum media.22,23 Researchers also noted that termination of these polymers with an amine or a diacrylate monomer unit had a dramatic effect on delivery.23–25 To further explore this effect, diacrylate-terminated PBAE C32 was reacted with 36 different amines and the impact of these modifications on DNA binding

9.24.3.2

PEI-Derived Polymers

Thomas et al.27 envisioned higher MW PEI analogues with lower toxicities by cross-linking small PEI fragments with degradable diacrylate esters. Small, low-MW PEIs have lower toxicities than high-MW PEIs. However, these smaller PEIs are poorer DNA binding and delivery agents than the higher MW analogues. In an effort to identify PEI derivatives with the relative advantages of both low- and high-MW PEIs, researchers combined a linear 423 Da PEI and a branched 1.8 kDa PEI with 24 diacrylate esters at three different molar ratios to create a combinatorial library of 144 biodegradable materials. Stock solutions of linear or mixed PEI in DMSO were combined with diacrylate esters in glass vials and stirred for 48 h at

120 000

100 000

RLU

80 000

60 000

40 000

20 000

er

/D

N A

100 60 30

Po l

ym

20

DNA

C32-Ac

PEI

10

C32

123

124

118

121 122

116

117

106

110

111 115

C32-X polymer

107 108 109

104 105

101 102 103

96 98 99

87 93 94 95

17 24 28 32 36 52 60 66 68 69 86

0

Figure 7 DNA transfection efficiencies in COS-7 cells of an end-modified PBAE (C32). Measurements were taken at five different DNA/polymer ratios with higher luminescence (RLU) correlating with increased DNA transfection. Reprinted from Zugates, G. T.; Tedford, N. C.; Zumbuehl, A.; et al. Bioconjugate Chem. 2007, 18 (6), 1887–1896,24 with permission from the American Chemical Society.

463

High-Throughput Approaches

1.2 1.0 Unmodified PE125

0.8 0.6 0.4

DNA binding (F ) r

65 °C. These conditions allowed for complete consumption of cross-linking agent. PEI-derived polymers were screened for transfection of a β-galactosidase-expressing plasmid into COS-7 monkey kidney cells.27 Potent transfection agents were then screened for toxi­ city in A549 human lung cancer cells, and then in vivo for systemic gene delivery in a mouse model. For in vitro transfec­ tion screens, polymers were diluted in sodium acetate buffer and complexed with DNA at different polymer to DNA ratios in a 96-well format. Nine different polymers were identified from the transfection screen that showed substantial enhancements over their starting reagent PEI, with one polymer showing a 2.5-fold improvement over 22 kDa PEI.27 All nine polymers showed high cellular viability (90%) in an MTT (3­ (4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay even at the highest concentration tested and significantly lower toxicity than 22 kDa PEI. The cross-linked PEIs did, how­ ever, show slightly more toxicity than the parent PEI molecules. Finally, these polymers were tested in vivo for the systemic delivery of a luciferase-expressing plasmid in a mouse model. Two nontoxic PEI derivatives mediated high levels of expres­ sion in the lungs, while one polymer displayed preferential expression in the spleen. Van Vliet et al.28 adopted a different approach to improving the transfection properties of PEI by combinatorially modify­ ing 25 kDa branched PEI. Four-hundred and thirty-five derivatized PEI polymers were synthesized in a 96-well microplate format through combinations of methylation, ben­ zylation, and n-dodecylation at various equivalents. These modifications altered the hydrophobicity and amine pKa, and introduced positively charged quaternized amines. To study the effect of these combinatorial modifications, modified PEIs were evaluated in three different assays: (1) for their ability to transfect a green fluorescent protein-encoding plasmid (pEGFP-C1) into CHO-K1 cells; (2) for toxicity by staining nonviable cells with propidium iodide; and (3) for their ability to form complexes with DNA in an ethidium bromide displa­ cement assay (Figure 8). The evaluation of the entire library represented approximately 5200 individual measurements, providing a rich data set for structure–activity correlations. Almost one-fourth (24%) of the library demonstrated greater green fluorescent protein expression levels than unmodified PEI, and these polymers did not exhibit cellular toxicity.28 DNA binding was observed with both high-transfection and toxic polymers. Synergistic improvement of transfection was observed with dually modified polymers, displaying the ability of combinatorial methods to not only generate materials with enhanced properties but also lead to the formulation of hypotheses for mechanistic understanding of relevant material properties.28 Barua et al.29 also adopted a combinatorial approach to improve on the delivery properties of PEI. A library of 80 polymers was synthesized by the ring-opening reaction between diglycidyl ethers and amines (Figure 9). Eight digly­ cidyl ethers were combined with 10 amines in equimolar ratios and polymerization was carried out in glass vials for 16 h. A ninhydrin assay was implemented to monitor the disappearance of reactive primary and secondary amines dur­ ing the course of the reactions.29 GPC and FTIR characterized the final polymer products. Polymers were first screened for their ability to bind DNA in an ethidium bromide

0.2 0

0

5 (%

0.0

5

10 lls Toxic sta ity ine dw it

15

15 hP

I)

20

20 (%

)

FP n tio n G fec ssio s n e Tra xpr se ell

10

ce

c

Figure 8 Transfection efficiency, toxicity, and DNA-binding data for all 435 derivatized PEIs. Reprinted from Van Vliet, L. D.; Chapman, M. R.; Avenier, F.; et al. ChemBioChem 2008, 9 (12), 1960–1967,28 with permission from Wiley.

displacement assay, with strong DNA binders being used in a DNA in vitro transfection assay. Seven polymers were identi­ fied as having representative DNA-binding strengths, low to strong, from the ethidium bromide displacement assay and were tested for transfection of PC3-PSMA cells.29 The successful delivery of pGL3 plasmid resulted in increased luciferase activity in transfected cells (Figure 10). Polymers with 1,4-bis(3-aminopropyl)piperazine (1,4Bis) as the amine monomers displayed higher efficiencies than PEI in this screen, with the combination of 1,4-cyclohexanedi­ methanol diglycidyl ether (1,4C) and 1,4Bis performing comparably or better than PEI at a number of DNA/polymer ratios. This trend continued for this polymer even in the pre­ sence of serum, and in an MTT assay the polymer displayed less toxicity than PEI at all tested concentrations.29

9.24.3.3

Lipidoids

Cationic lipid–nucleic acid complexes (lipoplexes) are a viable strategy for DNA/RNA delivery.30–32 Lipofectamine, a commer­ cially available mixture of cationic lipids, is still widely used and considered a standard for the in vitro delivery of nucleic acids into cells. However, the in vivo application of Lipofectamine has been extremely limited due to concerns over systemic toxicity. Of particular interest for therapeutic delivery is siRNA, which is an �22-nucleotide stretch of double-stranded RNA that activates the catalytic cellular machinery to selectively target specific mRNA sequences for degradation. By catalyzing the degradation of mRNA sequences, this process effectively stops cellular production of the corresponding protein, which could be a useful tool in the treatment of several diseases. Successful systemic delivery of siRNA to the liver in mice and nonhuman primates has been achieved using lipid formu­ lations, but lingering concerns over efficacy inspired Akinc et al.30,31 to adopt a combinatorial library approach to the synthesis and screening of novel cationic lipid formulations.

464

High-Throughput Approaches

(a)

(b) PEGDE PPGDE 4VCD GDE EGDE NPGDE 1,4B 1,4C

% Fluorescence decreased

70 60 50 40 30

Pentaethylene hexamine Diethylenetriamine 3,3’-diamino-N-methyldipropylamine N-(2-Aminoethyl)-1,3-propanediamine 1,4-Bis(3-aminopropyl) piperazine 4,7,10-Trioxa-1,13-tridecanediamine Ethylenediamine 1-(2-aminoethyl) piperidine n-Butylamine Aniline

20 10 0

Amine

PEGDE

PPGDE

Diglycidyl ether

4VCD

GDE

EGDE

NPGDE

1,4B

1,4-Cyclohexanedimethanol diglycidylether (1,4 C)

1,4C

Branched cationic polymer D i Poly(ethyleneglycol) diglycidylether (PEGDE) g l Poly(propyleneglycol) diglycidylether (PPGDE) y c 4-Vinylcyclohexene diepoxide (4VCD) d y Glycerol diglycidylether (GDE) l e t Ethyleneglycol diglycidylether (EDGE) h Neopentylglycol diglycidylether (NPDGE) e r 1,4-Butanediol diglycidylether (1,4 B) s

(Poly)amines

Parallel

screening of

DNA binding

efficacy

Figure 9 (a) Ring opening of diglycidyl ethers with amines as a strategy for generating a cationic polymer library. (b) DNA-binding efficiency for the cationic library was determined using an ethidium bromide displacement assay. Increased DNA binding results in decreased fluorescence. Reprinted from Barua, S.; Joshi, A.; Banerjee, A.; et al. Mol. Pharm. 2009, 6 (1), 86–97,29 with permission from the American Chemical Society.

By manually combining alkyl-acrylates or alkyl-acrylamides with primary or secondary amines, researchers were able to synthesize over 700 ‘lipidoids’ (lipid-like delivery molecules; Figure 11). The choice of monomers in this library allowed investigators to systematically examine a number of structural parameters: (1) alkyl chain length; (2) an amide versus an ester linkage; (3) amine diversity; and (4) the effect of quaterniza­ tion of the amine by reacting lipidoids with methyl iodide (MeI) post-synthesis. As an in vitro evaluation of this lipidoid collection, Akinc et al.30,31 used a HeLa dual-luciferase expression system. This cell line expresses two forms of the luciferase enzyme, Renilla (Renilla reniformis) luciferase and firefly (Photinus pyralis) luci­ ferase. Successful delivery of anti-firefly siRNA by siRNA/ lipidoid complexes results in decreased firefly luminescence, while Renilla luminescence should remain unchanged (a decrease in Renilla luminescence could be caused by cellular toxicity of the material). Effective lipidoids followed several trends, such as more than two amines per head unit, two long alkyl chains (i.e., 16 carbon), or many short alkyl chains (i.e., 12 carbon). To further investigate the impact of these trends on siRNA delivery, a second-generation library of 500 lipidoids was synthesized. This second library included more amines per monomer head unit and several shorter (< 12 carbon) alkyl chains. Since these lipidoids were capable of multiple substitution patterns given the greater number of amines per monomer, stoichiometry was also varied to gener­ ate materials with a diverse number of alkyl chains. Four different siRNA to lipidoid ratios were examined for each

material in this second-generation library, and all combina­ tions were performed in quadruplicate in the same HeLa dual-expression luciferase assay (Figure 12). Fifty-six lipidoids were identified from this screen that performed comparably to Lipofectamine 2000 in silencing luciferase expression. Top-performing lipidoids shared a number of structural fea­ tures, including amide linkages, more than two alkyl chains which are 8–12 carbons in length, and at least one secondary amine. Further examination of these top-performing lipids in HepG2 and primary bone marrow-derived murine macro­ phages demonstrated that these lipidoids had very low toxicity in their effective concentration range. A liver-directed rodent screen examined the in vivo efficacy of these top-performing lipidoids by measuring the gene silen­ cing of Factor VII, a blood-clotting factor that is produced exclusively in hepatocytes.30,31 Since Factor VII is a secreted protein, successful gene silencing can be determined by mea­ suring the serum levels of the protein. The top 17 best-performing lipidoids were formulated with Factor VII siRNA, cholesterol, and PEG-lipid. These additional compo­ nents for formulation were necessary to help ensure serum stability of ionic complexes, which generally suffer from aggre­ gation and poor stability in vivo. Seven lipidoids that significantly reduced the serum levels of Factor VII were identi­ fied. Investigators were also able to formulate these lipidoids simultaneously with two different siRNA molecules targeting two different hepatocyte-produced proteins, demonstrating the versatility of their materials. The lipidoid that produced the most dramatic reduction in the serum levels of these proteins

High-Throughput Approaches

(a)

p = 0.0006

(b) 100

RLU per mg protein relative to pEl-25

100

RLU per mg protein relative to pEl-25

465

P= P = 0.04 P = 0.007 0.052

10

1

0.1

10

1

1,4C-1,4Bis

NPGDE-1,4Bis

EGDE-1,4Bis

EGDE-3,3′

PPGDE-1,4Bis

EGDE-DT

EGDE-N-2amino

pEl-25

pEl-750

0.1 1

5

10

20

25

Polymer: pGL3 Plasmid ratio (w/w)

Polymer (d)

(c)

100

RLU per mg protein relative to pEl-25

p = 0.002

10

1

RLU per mg protein relative to pEl-25

100

p = 0.005 10

1

0.1 pEl-25 1,4C-1,4Bis

NPGDE-1,4Bis

EGDE-3,3′

EGDE-1,4-Bis

pEl-750

pEl-25

0.1

1,4C-1,4Bis

Polymer

Polymer Figure 10 Transfection efficiency measurements in PC3-PSMA cells with lead polymers from the primary DNA-binding screen. Luminescence levels are normalized against total protein and reported relative to PEI. (a) Transfection measurements in the absence of serum at a polymer/plasmid ratio of 25:1. (b) Transfection of plasmid DNA with 1,4C-1,4Bis (1,4C: 1,4-cyclohexanedimethanol diglycidyl ether; 1,4Bis: 1,4-bis(3-aminopropyl)piperazine) polymer at five different polymer/plasmid ratios. (c) Transfection in the presence of serum at a polymer/plasmid ratio of 25:1. (d) Transfection of murine osteoblasts with 1,4C-1,4Bis polymer at a polymer/plasmid ratio of 25:1 in the presence of serum. Reprinted from Barua, S.; Joshi, A.; Banerjee, A.; et al. Mol. Pharm. 2009, 6 (1), 86–97,29 with permission from the American Chemical Society.

Figure 11 Synthesis of ‘lipidoids’ by a Michael addition reaction. Treatment with methyl iodide leads to quaternized amines.

also demonstrated efficacy in silencing relevant proteins in a variety of nonhepatocyte cell types. Effective silencing of RSV/A2 was observed in a mouse model of respiratory syncytial virus infection and that of CD45 in peritoneal macrophages. Finally, researchers were able to achieve silencing of ApoB serum levels in cynomolgus monkeys with a single intravenous injection of lipidoid-formulated siRNA directed at ApoB. In this example, an iterative combinatorial approach toward new material discovery resulted in efficacious delivery agents not

only with high in vitro transfection efficiency, but also with generality over multiple cell types and animal species. The ring-opening reaction of epoxides with amines is a high-yielding reaction that has been useful in generating materials for DNA delivery.29 In an effort to further improve on the efficacy of siRNA delivery with lipidoids, Love et al.32 manually synthesized a library of 126 lipid-like materials in a 96-well microplate by combining 14 polyamines and 9 alkyl epoxides. Structurally, this new class of lipidoids contain hydroxyl groups

466

High-Throughput Approaches

(a)

(b)

(c)

(d) (e)

Figure 12 In vitro evaluation of the lipidoid library for siRNA delivery. (a) Percent reduction of firefly luciferase expression in HeLa cells with lipidoid/ siRNA formulations. The data are split into five groupings spanning 0–100% luciferase reduction for ease of analysis. (b) Optimal knockdown levels in HeLa determined by screening at four different lipidoid/siRNA ratios. (c–e) Dose response silencing in HeLa (c), HepG2 (d), and primary macrophage (e) cells. Reprinted from Akinc, A.; Zumbuehl, A.; Goldberg, M.; et al. Nat. Biotechnol. 2008, 26 (5), 561–569,31 with permission from the Nature Publishing Group.

that are not present in the acrylate-amine-derived lipidoids, but both classes of materials allow for the number of lipid ‘tails’ to be varied by stoichiometric control. By adopting the library screening approach outlined by Akinc et al.,30,31 researchers were able to identify one lipidoid with in vivo delivery efficacy that was an order of magnitude greater than that of previously identified potent lipidoid agents (Figure 13). This considerable improvement in delivery efficacy greatly widens the therapeutic index of the material, making the outcome of this combinator­ ial experiment highly germane for future medical applications of siRNA therapy.

9.24.4 Organic Coatings Organic coatings have considerable utility in numerous indus­ trial, commercial, and academic applications and are composed of complex materials.1,7,33 Our inability to accu­ rately predict the properties of such complex materials, let alone how these materials interact with their environments, makes applying a combinatorial approach to this problem highly attractive. A number of research groups, both academic and industrial, have developed high-throughput methodology to develop next-generation coatings for a variety of different applications, and we highlight those approaches here. General Electric first described combinatorial approaches to develop clear coatings for plastics.34–37 A methodology for synthesizing and evaluating 100–200 new coatings a day could be examined in a 48-element arrayed workflow. Automated liquid dispensing was used to dispense coatings onto a silicone-templated plastic substrate, where they were cured with heat or UV radiation after being spread evenly in

the reservoirs. Using a suite of customized high-throughput instruments, investigators were able to screen these coatings for optical clarity, adhesion, resistance to weathering, and abra­ sion resistance. These high-throughput techniques were found to correlate well with standard industry coating measurements such as the Taber abrasion test and the crosshatch adhesion test. While few details are given on the compositions of these coatings, the GE workflow is an interesting case study of the challenges and planning required in high-throughput coating development. Researchers at North Dakota State University (NDSU) have developed an impressive high-throughput platform to discover new marine fouling-release coatings by working closely with Symyx, a company that specializes in laboratory automa­ tion.7,38–43 This research is particularly germane to the maritime industry, since biological fouling of ship hulls by marine life impairs a sea ship’s performance and maneuver­ ability. Several libraries of siloxane-polyurethane coatings were designed and constructed using Symyx Library Studio software and a customized Symyx core module (Figure 14). These libraries were analyzed for four main parameters: the MW of poly(dimethylsiloxane) (PDMS), both the presence and length of poly(ε-caprolactone) (PCL) blocks, and the siloxane polymer levels present in the coatings. These siloxane polymers were then formulated using automated liquid handling with a trifunctional isocyanate cross-linker, a trifunctional PCL polyol, 2,4-pentanedione, and dibutyltin diacetate, and were incubated with a range of solvents in vials until sufficient viscosity was achieved for coatings. A Symyx coating application system then robotically applied coatings in a specialized Q panel 3 � 4 array format. After allowing the coatings to dry overnight and curing for 45 min at 80 °C, surface energy measurements were

High-Throughput Approaches

467

Figure 13 Structure of C12-200, the highly efficacious siRNA delivery agent identified in Reference 32.

(a)

Increase Mn for PDMS

(b) Increase PCL length

PDMS

Polyurethane

1

2

4

3

5

6

A B C D

In

cr

ea s co e s nt ilo en xa t ne

5000

5000

7500

7500

10 000

15 000

20 000

25 000

30 000

35 000

1

2

3

4

5

6

1

2

3

4

5

6

2 CLs B 3 CLs C 4 CLs D

Increase Mn for PDMS

0 CL

A

2 CLs B 3 CLs C 4 CLs D

Increase PCL length

A

Increase PCL length

0 CL

2500

(c)

2500

Epoxy primer

Increase Mn for PDMS

Figure 14 (a) Cross section of a self-stratified siloxane-polyurethane coating. (b) Library design for coating formulations. (c) Library design for the synthesis of both low- and high-MW siloxanes. Adapted from Ekin, A.; Webster, D. C. J. Comb. Chem. 2007, 9 (1), 178–188,40 and reprinted with permission from the American Chemical Society.

performed using a Symyx coating surface energy system and pseudobarnacle adhesion measurements were taken using a Symyx automated pull-off adhesion system.

Evaluation of the coatings after 30 days of water treatment for surface energy and pseudobarnacle adhesion revealed that while the triblock PDMS-PCL-PDMS coatings had lower surface

468

High-Throughput Approaches

Initial average force at release (N)

(a)

Number of caprolactones per amine − 0

Number of caprolactones per amine − 2

Number of caprolactones per amine − 3

Number of caprolactones per amine − 4

50 45 40 35 30 25 20 15 10

50 45 40 35 30 25 20 15 10 5

10

15

20

25

30

35

40

45

5

10

15

20

25

30

35

40

45

% siloxane added

Average force at release after water immersion (N)

(b)

Number of caprolactones per amine − 0

Number of caprolactones per amine − 2

Number of caprolactones per amine − 3

Number of caprolactones per amine − 4

50 45 40 35 30 25 20 15 10

50 45 40 35 30 25 20 15 10 5

10

15

20

25

30

35

40

45

5

10

15

20

25

30

35

40

45

% siloxane added Figure 15 Pseudobarnacle adhesion test results (a) before water immersion and (b) after water immersion. Large data points correspond with high-MW polymers used in the coating. Adapted from Ekin, A.; Webster, D. C. J. Comb. Chem. 2007, 9 (1), 178–188,40 and reprinted with permission from the American Chemical Society.

energies than 3-aminopropyl-terminated PDMS coatings, they resulted in more pseudobarnacle adhesion than the 3-aminopropyl-terminated PDMS coatings (Figure 15).40,41 Increased siloxane polymer content resulted in increased pseu­ dobarnacle adhesion but had no impact on surface energy. Since it is generally believed that coatings with lower surface energies should have lower pseudobarnacle adhesion, the PDMS-PCL-PDMS coatings that displayed lower surface ener­ gies but higher adhesion levels were especially notable. An expanded study encompassed 288 coatings and imple­ mented a similar platform but also included live barnacle, algal, and bacterial adhesion tests.41 Eight positives from the initial screen were characterized by DSC, dynamic mechanical analysis, XPS, and surface energy analysis. These methods con­ firmed the composition and structure of these lead candidates. Two coatings of the eight lead candidates performed well in all three live fouling experiments: algal (Ulva), bacterial

(Cytophaga lytica, Halomonas pacifica), and barnacle (Balanus amphitrite). These two coatings were deemed appropriate to begin ocean testing. NDSU researchers have also looked at coatings for different applications. Nasrullah et al.44 used a Chemspeed Autoplant A100 to demonstrate the first automated synthesis of water­ borne polyurethane dispersions (PUDs), which are useful coatings for a large variety of applications such as wood finish­ ing, glass fiber sizing, adhesives, automotive topcoats, and many more. The synthesis of these dispersions can be challen­ ging, since there are a large number of parameters, both compositional (reactivity and behavior of different isocyanates, amines, and catalysts) and process-related (temperature, heat­ ing, cooling, and type of stirring), that can drastically affect synthetic outcome. While the library size (24) was relatively small, a number of variables were able to be optimized, and characterization of PUDs for particle size, viscosity, and percent

High-Throughput Approaches

solid demonstrated that the results from automated methods were not only comparable with those of conventional benchtop methods, but were also far more consistent. Kugel et al.45 developed novel polyurethane coatings with antimicrobial properties by tethering biocide moieties to a polymer matrix. Researchers used the Symyx automated plat­ form at NDSU to make an array of 24 copolymers with varied amounts of three monomers of butyl acrylate (BA), hydro­ xyethyl acrylate (HEA), and triclosan acrylate (TA). Characterization of this polymer array by NMR, GPC, and DSC revealed that TA monomer content correlated directly with increased glass transition temperature but inversely with increased MW. Blending of these acrylic polyols with hexam­ ethylene diisocyanate trimer in the presence of a tertiary amine catalyst yielded 24 polyurethane coatings in a 24-array format. These coatings were tested for antimicrobial properties against C. lytica, Staphylococcus epidermidis, Escherichia coli, and Nitokra incerta using a Tecan EVO Freedom 200 liquid handling system with a customized deck for screening libraries in a 24-well array format. Coatings that contained a relatively low amount of HEA monomer but high amounts of TA monomer showed the best antimicrobial properties toward S. epidermidis, a Gram-positive bacterium often associated with infection related to the implantation of medical devices. The effective­ ness of this coating makes it an attractive candidate for use as a coating of medical devices as a means of preventing these infections.

9.24.5 Polyolefin Catalyst Discovery Polyolefins are a highly versatile polymer class used in a num­ ber of commercial applications. The discovery of more selective and efficient catalysts for polyolefin synthesis is a constant demand, and high-throughput experimentation has received considerable attention to meet this need.2,46 Many of the tech­ niques developed to identify these catalysts closely mirror the methods used in small-molecule drug discovery and may not be generally applicable to the combinatorial polymer generation. Solid-phase methods have been utilized by a number of groups to synthesize a library of ligand–metal complexes and to aid in the rapid identification of lead catalysts. In two separate reports, Boussie et al.47,48 at Symyx Technologies used a functionalized polystyrene solid support to immobilize 48 different diimine ligands and then complex them with either nickel(II) or palladium(II) metals. This collection could then be queried in a spatially addressed manner by exposing the activated beads to ethylene in a high-pressure parallel reac­ tor. Effective catalysts could be identified by the formation of large polyethylene granules that form around the individual beads. Overall, nickel-based catalysts yielded polymers with higher yields and MWs than the palladium-based equivalents. However, solid-supported palladium-based catalysts had higher reactivity than their solution-phase analogs while nickel-based systems did not. To determine whether a pooled screening approach could be adopted, the solid-supported metal–ligand complexes were further reacted with secondary amine tags that encoded the chemical history of each library member. The identity of the diimine ligand and the metal used for the respective library

469

member is encoded by the two substituents of the secondary amine tag. The encoded beads were then placed under a high pressure of ethylene in a single reactor to initiate polymeriza­ tion. Again, successful polymerization was visually determined by the formation of a large granule around the solid support, and investigators demonstrated that the catalysts can be identi­ fied by subsequent cleavage of the tags associated with granule-covered beads followed by high-performance liquid chromatography (HPLC) analysis. This pooled approach was also explored by Stork et al.49 to analyze the efficiency of zirconium complexes in polyolefina­ tion. Instead of secondary amine tags, fluorescent tags were used for chemical encoding of the solid-supported catalysts to allow for easier identification of active catalysts from the pooled mixture. Both catalyst and dye were immobilized onto silica beads through an impregnation method, and sub­ sequent screening revealed that the most efficient catalyst produced a monomodal polyethylene distribution with an MW of 207 kDa and a PDI of 2.24. Tian and Coates50 also adopted the pooled approach, but without using a solid sup­ port, to identify catalysts that produce syndiotactic polypropylene. A 12-ligand library was synthesized by combin­ ing three salicylaldehydes with four anilines to form salicylaldimines. Treatment of these ligands with a strong base and titanium tetrachloride yielded metal–ligand com­ plexes to be used in the screen. These complexes were pooled together after activation and pressurized with propylene to initiate polymerization. Since syndiotactic and atactic polymers can have differential solubility, the insoluble polymer in the reaction mixture was hypothesized to be syndiotactic polypro­ pylene. Since there was no encoding strategy, deconvolution of the catalyst mixture by analyzing the polymerization of several smaller sublibraries allowed researchers to isolate the catalyst of interest. While the mechanism of this catalyst is not described, the outcome is the first illustration of the use of combinatorial methods to obtain stereochemically defined polymers. In an effort to discover new single-site catalysts for olefin copolymerization, Boussie et al.51 at Symyx Technologies devel­ oped an integrated and automated workflow to rapidly synthesize and evaluate potential catalysts. Data collection and analysis were greatly facilitated by a high-throughput GPC and FTIR analysis of reaction products. To validate the primary screening approach, the well-studied [(η5-C5Me4) SiMe2(η1-NBut)]TiMe2 catalyst was used for the polymeriza­ tion of 1-octene with the same four catalyst activators, catalyst concentrations, and reaction scale to be used in the primary screen (Figure 16). Excellent reproducibility was obtained as well as re-creation of known performance features of the [(η5-C5Me4)SiMe2(η1-NBut)]TiMe2 catalyst, validating the pri­ mary screen approach. A diverse collection of 24 ligands were complexed with two different group IV metals (Zr and Hf) and tested with four different catalyst activators for a total of 384 unique parameter combinations for the polymerization of 1-octene. Ten metal–ligand complexes with the appropriate activators were identified from this primary screen for high monomer conversion, with one Hf/ligand/activator combina­ tion yielding near 100% conversion. To improve upon the performance of this catalyst complex, a focused 96-membered library of structural analogs to the ligand was used in a secondary screen (Figure 17).51 In this

470

High-Throughput Approaches

Me Me2Si

Ti

Bu

C

Me

N

8 Replicates

B

D E

t

F

Catalyst for primary screen validation

G

Monomer: 120 μl 1-octene

H

Total volume: 220 μl

SPACING = 9 MM (0.3543 IM)

SMX-10000-1 REV.A

1

Column no.

2

3

4

5

6

7

8

9 10 11 12 +

None (control)

Four activation zones Three catalyst concentrations (mM)

200 eq. MAO

[Me2PhNH]

+

−

[B(C6F5)4]

[Me2PhNH]

−

[B(C6F5)4] +

5 eq. Bui3Al

1.8 0.18 .018 1.8 0.18 .018 1.8 0.18 .018 1.8 0.18 .018

Figure 16 Design of the primary screening validation experiment. Reprinted from Boussie, T. R.; Diamond, G. M.; Goh, C.; et al. J. Am. Chem. Soc. 2003, 125 (14), 4306–4317,51 with permission from the American Chemical Society.

600 NH

O

[7F]

500

NH

O

Yeild (mg)

400

300 NH

O

O

200 F3C

100

0 0

50

100

150

200

250

300

350

400

450

MW (K)

NH

O

Initial primary screening discovery

Wt % 1-octene range 10 – 20% Wt % 1-octene range 0 – 10%

Figure 17 Polymer MW and yield from ethylene 1-octene copolymerizations with the secondary, focused catalyst library. Reprinted from Boussie, T. R.; Diamond, G. M.; Goh, C.; et al. J. Am. Chem. Soc. 2003, 125 (14), 4306–4317,51 with permission from the American Chemical Society.

screen, all 96 reactions were tested for the copolymerization of 1-octene with ethylene on a much larger scale at 130 °C in a customized, automated parallel pressure reactor. The results from this screen revealed a strong dependence between polymer yield, MW, and 1-octene incorporation. Copolymers also possessed low PDIs, supporting a single-site catalyst

mechanism. A large number of catalyst complexes could be identified from this screen with superior performance over the catalyst complex identified from the primary screen. Further validation of this approach was demonstrated by the comparison of two highly active complexes from these screens to a commonly used industrial polyolefin catalyst on a

471

High-Throughput Approaches

commercially relevant one liter scale batch polymerization reactor. These new Hf-based catalyst systems performed com­ parably and even outperformed the industrial standard in several areas. Solution-phase approaches have been successfully adopted by a number of other groups in order to both discover and optimize olefin polymerization catalysts. Mason and Coates52 used GPC on polymer mixtures from pooled catalyst libraries in order to identify active heteroligated phenoxyimine titanium catalysts. Hinderling and Chen53 reported electrospray ioniza­ tion tandem mass spectrometry (ESI-MS/MS) as a means of identifying palladium catalyst complexes in pooled libraries. Adams et al.54 analyzed a library of 50 imidotitanium com­ plexes for ethylene polymerization, and identified seven active complexes. Finally, in a study by Jones et al.55,56 a library of 205 salicylaldimine-chromium complexes were evaluated for ethy­ lene polymerization. Highly active chromium catalysts were identified with ligands that could direct the formation of both high- and low-MW polyethylene.

9.24.6 Polymers Generated through Radical Polymerization Radical-mediated polymerization techniques have seen great advances in the last few decades in large part due to the rapid development of controlled/living radical polymerizations. Atom-transfer radical polymerization (ATRP), reversible addition-fragmentation chain transfer (RAFT), and nitroxide­ mediated polymerization (NMP) are examples of living/ controlled radical polymerization techniques that allow for the synthesis of polymers with well-defined compositions, function­ alities, and architectures.4,5 Studies in the last decade began to apply high-throughput experimentation for the optimization and implementation of these techniques, and are reviewed below according to the class of radical polymerization used.

9.24.6.1

Atom-Transfer Radical Polymerization

ATRP is a versatile process to effect polymerization and utilizes transition metal complexes to maintain equilibrium between the active and dormant forms of a propagating polymer chain.57–60 However, the involvement of several parameters (catalysts, ligands, monomers, temperatures, ratios, and sol­ vents) can make optimization of conditions for a particular process arduous. To address this issue, Zhang et al.59,60 demon­ strated the feasibility of implementing high-throughput methods with ATRP and screened a variety of polymerization conditions to optimize the process. Utilizing a Chemspeed ASW2000 parallel synthesizer, optimal ATRP reaction condi­ tions were screened for the polymerization of methyl methacrylate (MMA) in an automated fashion (Figure 18). By varying the metal salts, initiators, and ligands, researchers explored 108 different polymerizations of MMA. Reactions were performed in specialized jacketed glass reactor vessels that are supplied with the ASW2000 and which could be heated or cooled. Mixing of the reactors was performed by vortexing of the reactor blocks on-deck. An in-line GPC system was utilized for polymer analysis. Researchers further optimized purification of a model ATRP reaction using the same automated parallel synthesizer that was outfitted with a solid-phase extraction (SPE) unit that utilizes silica gel or aluminum oxide filtration cartridges that can interface with synthesizer’s liquid-dispensing system.58 The polymerization of MMA with p-toluenesulfonyl chloride (TsCl) as the initiator and CuCl/4,4′-dinonyl 2,2′-bipyridine (dNbpy) as the catalyst was chosen as a model reaction for this study. The PMMA polymer of this reaction was determined to have an MW of 12 000 Da and a PDI of 1.15. Sixty-four different purification conditions were analyzed by varying col­ umn materials, column lengths, and eluent collected. For the model reaction, a 1.5-cm-long activated neutral or basic alumi­ num oxide column with 2 ml of THF eluent was optimal.

(e) a a

SEC samples

GC samples

b

b SEC

(a)

(c) Reactor blocks

(b)

(d)

SPE unit

Stock solutions

EBIB

M N

M

N

M N

M N

M

N CB CL

PC

1

MBP

M N

M

N

M N

M

N

M

N CB CL

PC

2

BEB

M N

M

N

M N

M

N

M

N CB CL

PC

3

TsCl

M N

M

N

M N

M

N

M

N CB CL

PC

4

EBIB

H T

H

T

H T

H

T

H

T CC FB

5

MBP

H T

H

T

H T

H

T

H

T CC FB

6

BEB

H T

H

T

H T

H

T

H

T CC FB

7

TsCl

H T

H

T

H T

H

T

H

T CC FB

8

Figure 18 Automated ATRP. (a) Chemspeed ASW2000 with in-line gas chromatography and GPC. (b) View of the deck of the automated platform. (c) Filtration columns and the corresponding solid-phase extraction (SPE) unit. (d) ATRP of MMA in the glass reactors. (e) Schematic of the robot deck and combinations of metal salts, ligands, and initiators used in this study. Reprinted from Zhang, H. Q.; Marin, V.; Fijten, M. W. M.; Schubert, U. S. J. Polym. Sci., Polym. Chem. 2004, 42 (8), 1876–1885,60 with permission from Wiley.

472

High-Throughput Approaches

(d)

(a)

1

2

3

4

5

6

A

B

C

D (b)

(c) ATRP of Styrene and t-BA

Styrene Copper complex solution

t-BA

Anisole

Initiator solution

Figure 19 (a–c) Several views of the Symyx CM2 synthesis platform encased in a glove box. (d) Library design for the homopolymerization of styrene and t-BA. Adapted from Nasrullah, M. J.; Webster, D. C. Macromol. Chem. Phys. 2009, 210 (8), 640–650,57 and reprinted with permission from Wiley.

Researchers at NDSU used their Symyx-based automation system to implement ATRP in the polymerization of styrene and t-BA (Figure 19).57 Webster and co-workers wanted to investigate numerous issues surrounding the application of parallel automated ATRP: (1) evaluate the feasibility of their automated systems to carry out the polymerization of styrene and t-BA; (2) synthesize a range of different target MWs within the same library; (3) monitor the effect on ATRP with and without polymerization inhibitors; and (4) evaluate the result of continuing polymerizations in a reactor for extended periods after already achieving high conversions. The Symyx polymer synthesis station at NDSU is enclosed in a triple glove box purged with nitrogen, allowing reactions to occur under air-free conditions. Both 20 and 8 ml vials were used in these experiments in 6 � 4 arrays, with magnetic stir­ ring. In addition to conventional GPC, a Symyx rapid GPC system was used for robotic sample preparation, injection, and rapid analysis of polymer samples. A Genevac EZ-2 solvent evaporation system was used to remove bulk solvent and unreacted monomer prior to GPC analysis. Researchers obtained good agreement between theoretical and measured MWs in addition to low PDIs (Figure 20). High vial-to-vial reproducibility was observed for both monomers and the use of inhibitors did not significantly affect the polymerization outcome. Extending the polymerization time, however, did result in increased MW and PDI.

9.24.6.2

Reversible Addition-Fragmentation Chain Transfer

RAFT is a highly versatile method of polymerization that utilizes a chain-transfer agent (CTA) to produce the dormant form of the growing polymer chains.61,62 The CTA is com­ monly a di- or tri-thiocarbonylthio compound that forms a stabilized radical intermediate. Chain equilibration between actively growing and dormant chains leads to uniform rate of chain growth for all polymers, and is linearly related to con­ version. Since transition metal catalysts are not required, RAFT has increased compatibility with a wider array of monomer functionalities than other polymerization methods, but the

absence of oxygen is absolutely necessary to prevent premature termination of growing polymer chains. Fijten et al.61 first described the RAFT polymerization of MMA on a Chemspeed Accelerator SLT100 in 2004. The Accelerator is the successor of the ASW2000, and featured a four-needle head and a solid dosing unit while using the same jacketed glass reactor vessels used in the ASW2000. The RAFT polymerization of MMA was studied using azobis(isobutyroni­ trile) (AIBN) as an initiator and 2-cyano-2-butyldithiobenzoate (CBDB) as the CTA. Investigators queried several ratios of initiator to CTA with the same target MW to test reproducibility on the automated platform. Both GPC and MALDI time­ of-flight mass spectrometry (MALDI-TOFMS) confirmed the synthesis of polymers with well-defined MWs and narrow PDIs. The optimal temperature for polymerization was deter­ mined by measuring the effect of several temperatures on polymerization in terms of MW and PDI. Finally, researchers performed chain-extension experiments and demonstrated the feasibility of creating defined block copolymers in an auto­ mated manner. In a separate report, Paulus et al.63 used RAFT as a way to compare the performance of different automated synthesizers. Three Chemspeed platforms, an ASW2000, an Accelerator SLT100, and an Autoplant A100, all executed the RAFT polymerization of MMA under similar conditions, but at a 10-fold increased scale in the case of the A100. The Accelerator SLT100 is the successor to the ASW2000, and features added capabilities but operates on similar scales. The Autoplant A100 uses larger steel reactor modules that feature independently controlled mechanical stirrers that han­ dle increased viscosities (up to 30 Pa s) and temperature control. The authors observed good reproducibility between platforms, but did notice that the larger scale RAFT polymer­ izations on the Autoplant A100 had decreased MW relative to the other platforms. This result was attributed to poorer heat transfer between the reactor and the reaction mixture at the increased scale. In an expanded study, Fournier et al.64 used RAFT to make random N,N-(dimethylamino)ethyl methacrylate (DMAEMA) and poly(ethylene glycol) methyl ether methacrylate (PEGMA) copolymers utilizing their automated platform. Since both of

High-Throughput Approaches

473

(a) 50

30 20 10

6 5 Po ly

4 3 2 1

Po ly

Po ly

(st

yre

(st

yre

ne

Po ly ( t-

000

000

000

000

000

0

( t-

BA

)o

BA

)o

r ro w

ne

)o

r ro w

)o

Mn(Target)

40

r ro wA

r ro w

D

C

B

(c) 20 15

50

15

000

000

Mn(The o)

10

20

000

10 50

00

0

6 5

Po ly

4 3

Po ly

2 1

Po ly

(st

Po ly

4

A)

(t-B

yre

yre

5 3

A)

(st

Po ly

2 1

ne

)

Po ly

ne

)

(d)

000

000

00

0

6

(t-B

000

Mn(GP C)

(b)

(st

yre

Po ly

Po ly

(t-B

A)

(t-B

A)

(st

yre

ne

)

ne

)

(e) 1.2

80

40 20

6 5 4 3

Po ly

2 1

Po ly

(st

yre

Po ly

Po ly ( (t-B

ion

0

yre

1.1

t-B

A)

ne

)

ne

)

5

0

1.0

5

6

A)

(st

1.1

% Convers

60

0

PDI

100

5

Po ly

4 3 2 1

Po ly

Po ly (t-B

1.0

0

(t-B

Po A) ly ( sty ren e) yre ne )

A)

(st

Figure 20 (a) Targeted, (b) theoretical, and (c) measured MWs of homopolymerizations. Also shown are monomer conversion (d) and PDI (e). Adapted from Nasrullah, M. J.; Webster, D. C. Macromol. Chem. Phys. 2009, 210 (8), 640–650,57 and reprinted with permission from Wiley.

these monomers are thermosensitive and DMAEMA is pH sen­ sitive, copolymerization should produce interesting ‘smart’ polymers. Monomers were polymerized in the presence of AIBN as a source of radicals and CBDB as the RAFT agent. Reactivity ratios were determined for both monomers, so the macromolecular structure could be better understood. Analysis of these ratios revealed preferential incorporation of DMAEMA during RAFT polymerization initiation and a gradient in mono­ mer composition (Figure 21). Eleven different concentrations of PEGMA resulted in copolymers that differed in PEGMA content and in measured lower critical solution temperatures (LCSTs). A strong correlation was observed between PEGMA content and LCST at three different pH conditions. Higher PEGMA content resulted in polymers with higher LCST values, which is consistent with the increased hydrophilicity. An

investigation of the surface energies of the copolymeric thin films showed no correlation between PEGMA content and sur­ face energy. Macromolecular design via the interchange of xanthates (MADIX), a process that is mechanistically analogous to RAFT, exclusively utilizes xanthates as CTAs to mediate a con­ trolled radical polymerization.65 Chapon et al.65 described the synthesis of diblock and homopolymers using a Chemspeed ASW2000 as an automated platform. To establish the reprodu­ cibility of MADIX on an automated platform, two different xanthates (S-(1-ethoxycarbonyl)ethyl-O-ethyl xanthate and its trifluoroethyl derivative) and several xanthate concentrations were tested in the polymerization of BA and ethyl acrylate. Excellent reproducibility was observed between automated and conventional experiments with MWs agreeing with

474

1.0

η = 1,400ξ −0.74222

0.8

R2

(b) 80

= 0.9901

0.6

70

0.4

60

LCST (°C)

(a)

High-Throughput Approaches

η

0.2 0.0 −0.2

pH 4 pH 7 pH 10

50 40

−0.4 −0.6

30

−0.8

20

−1.0 0.0

0.2

0.4

0.6

0.8

1.0

0

20

ξ

40

60

80

100

wt.% PEGMA in the copolymer

Surface energy (mN m−1)

(c) 50

45

40 35 30 25 20 0

20

40

60

80

100

wt.% PEGMA

Figure 21 (a) Calculated reactivity ratios for DMAEMA and PEGMA monomers in RAFT polymerization. (b) Dependence of lower critical solution temperature (LCST) on PEGMA polymer composition and pH. (c) Calculated surface energies of copolymer thin films. Adapted from Fournier, D.; Hoogenboom, R.; Thijs, H. M. L.; et al. Macromolecules 2007, 40 (4), 915–920,64 and reprinted with permission from the American Chemical Society.

expected values and PDIs between 1.4 and 1.9. The copolymer­ ization of ethyl acrylate with BA yielded well-defined diblock polymers with narrow MWs and PDIs.

9.24.6.3

Nitroxide-Mediated Polymerization

Analogous to ATRP and RAFT, NMP is a controlled radical process that creates equilibrium between dormant and propa­ gating polymer chains, which limits premature termination or transfer reactions. However, while ATRP utilizes a metal halo­ gen catalyst and RAFT implements a sulfur-containing CTA, NMP uses an organic alkoxyamine (also called a nitroxide) as a reagent for radical initiation and to maintain chain propaga­ tion. While ATRP and RAFT can achieve a superior control over polymer growth over a wider array of monomers than can NMP, the low environmental impact of the controlling agent makes NMP a more industrially attractive process that can easily be implemented with automated methods. Researchers at IBM in collaboration with Symyx and University of California, Berkeley, investigated the use of NMP to generate functionalized nanoparticles.66 Since α-hydrido-based alkoxyamines preferentially incorporate sub­ stituted maleimides during the copolymerization of styrene/ maleimide mixtures, researchers used this as their model

system. When a polystyrene-based macroinitiator initiates the polymerization of a mixture of 1,1′-(methylenedi-4,1-pheny­ lene)bismaleimide (BMI) and styrene, investigators produced a cross-linked BMI core with random styrene spacers, which effectively brings together the polymeric arms of the polystyr­ ene regions leading to the formation of a soluble star polymer. However, despite the added control over reactivity offered by NMP, initial attempts to form star polymers yielded highly polydisperse structures with a large amount of unreacted macroinitiator. To determine the optimal reaction conditions to generate ‘star’ polymers, investigators adopted a high-throughput combinatorial approach and screened 384 different conditions. This library approach probed several key parameters involved in star formation: (1) MW of the linear arms of the stars; (2) the amount of cross-linking agent; (3) the type of cross-linking agent; (4) the use of comonomer; and (5) the effect of concentration and solvent.66 Using a Symyx core mod­ ule and a 96-well aluminum-cast glass vial reactor, the entire library of reaction conditions could rapidly be set up in 2–4 h. Automated optimization of the styrene/BMI ratio was first carried out by testing the full matrix with different molar equivalents of each component under constant temperature

High-Throughput Approaches

and incubation time. Nine different outcomes were observed when this matrix was analyzed by GPC, and the optimal con­ dition yielded high-MW, well-defined stars. With the success of optimizing these conditions, the researchers moved to evaluat­ ing matrices of other parameters in this reaction such as the MW and amount of the macroinitiator and the type of cross-linking agent. The evaluation of so many parameters in the reaction not only allowed the investigators to obtain opti­ mal reaction conditions, but also helped them to identify the salient factors for producing star polymers in this manner. Other reports have utilized automated, high-throughput experimentation for optimizing NMP in slightly different con­ texts.67,68 Eggenhuisen et al.69 made use of their Chemspeed ASW2000 to take a combinatorial approach to tuning the LCST behavior of poly(2-hydroxypropyl acrylate) (P(HPA)). LCST is a defining property of thermoresponsive polymers, and poly­ mers with a low LCST have a tendency to show a reversed solubility profile in water; at temperatures below the LCST, the polymer is solubilized in water, while high temperatures induce a hydrophobic collapse and precipitation of the poly­ mer. This phase transition is correlated to the hydrophilic/ hydrophobic balance in a polymer, and therefore copolymer­ ization of monomers with different hydrophobicities/ hydrophilicities is an attractive strategy to obtain polymers

0% R = 0.990

3% R = 0.999 6% R = 0.998 10% R = 0.995 15% R = 0.992 20% R = 0.992

6

Ln(M0 /Mt)

5

4

3

with different LCSTs. P(HPA) has an LCST of 16 °C, so investigators hypothesized that copolymerization with more hydrophobic monomers would produce polymers with a range of LCSTs. The need for narrow MW distributions to have sharp LCST transitions and the availability of effective nitroxide/alkoxyamine initiator pairs made NMP an attractive choice for the copolymerization of 2-hydroxypropyl acrylate (HPA) with the more hydrophilic monomers N,N-dimethyla­ crylamide (DMA) and N-acryloylmorpholine (Amor). In order to establish optimal conditions for copolymerization, a kinetic analysis was performed on the homopolymerizations of each of the three monomers using the ASW2000 automated synthe­ sizer and GPC for MW determination (Figure 22). Six different percentages of initiator were tested for each monomer homopolymerization, with ideal conditions determined to be 2 M dimethylformamide (DMF) solutions with 20% initiator and 8 and 5 h incubation time for Amor and DMA monomers, respectively. These conditions were used to synthesize two libraries of Amor and DMA copolymerizations with HPA, with 11 different monomer feed ratios being used to create polymers with vary­ ing hydrophobicity/hydrophilicity properties.69 GPC analysis of these libraries displayed a narrow MW distribution and low PDI, and measurement of thermal transitions using DSC

12 000

B-Amor 0% 3% 6% 10% 15% 20% Mn, th

10 000 8000

−1 Mn (g mol )

A-Amor

6000

4000

2000

2

0

1.8 1.6 1.4 1.2

0 2

4

6

8 10 Time (h)

12

14

16



0

C-DMA

5

4

40 60 Conversion (%)

80

100

D-DMA 0% 5% 10% 15% 20% Mn, th

8000 6000

Mn (g mol−1)

6

Ln(M0 /Mt)

10 000

0% R = 0.990 5% R = 0.993 10% R = 0.992 15% R = 0.989 20% R = 0.994

20

3

2

4000 2000 0

1.8 1.6 1.4 1.2

0

2

4

6

8 10 Time (h)

12

14

16

E-HPA

4

20

40 60 Conversion (%)

80

100

F-HPA 0% 5% 10% 15% 20% Mn, th

12 000 10 000 Mn (g mol−1)

Ln(M0 /Mt )

5

0

14 000

0% R = 0.993 5% R = 0.991 10% R = 0.977 15% R = 0.999 20% R = 0.969

6



3 2

8000

6000

4000

2000

0

1.8 1.6 1.4 1.2

0 0

2

4

6

8 10 Time (h)

12

14

16

0

20

40 60 Conversion (%)

80

100

PDI

1

PDI

1

0

PDI

1

0

475



Figure 22 Kinetic characterization of the homopolymerizations of Amor (a, b), DMA (c, d), and HPA (e, f) with different percentages of SG-1. Reprinted from

Eggenhuisen, T. M.; Becer, C. R.; Fijten, M. W. M.; et al. Macromolecules 2008, 41 (14), 5132–5140,69 with permission from the American Chemical Society.

476

High-Throughput Approaches

(a)

(b) 160 140 120

100 80

100

Tg (°C)

Tg (°C)

120

Tgexp p(Amor-stat-HPA) Tgcalc Fox Tgcalc linear

80 60

60 40

40 0

0 0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

HPA (wt. %)

HPA (wt. %) (d)

(c) 90

90

p(Amor-stat-HPA) 0.5 wt. % p(Amor-stat-HPA) 0.1 wt. %

80 Cloud point (°C)

80 Cloud point (°C)

Tgcalc Fox Tgcalc linear Tgexp p(Amor-stat-HPA)

20

20

70 60 50 40

70 60 50 40

30

30

20

20 30

40

50

60

70

80

90

100

HPA (wt. %)

p(DMA-stat-HPA) 0.5 wt. % p(DMA-stat-HPA) 0.1 wt. %

30

40

50

60

70

80

90

100

HPA (wt. %)

Figure 23 (a) Glass transition temperatures and (c) LCST of the Amor-HPA copolymer library and (b) glass transition and (d) LCST of the DMA-HPA copolymer library. Adapted from Eggenhuisen, T. M.; Becer, C. R.; Fijten, M. W. M.; et al. Macromolecules 2008, 41 (14), 5132–5140,69 and reprinted with permission from the American Chemical Society.

yielded glass transition temperatures for the two libraries that deviated positively from theoretical prediction, indicating the presence of hydrogen bonding (Figure 23). Analysis of the LCST behavior of the two copolymer libraries demonstrated that the cloud points for both copolymers could be tuned in the range of 20–100 °C. The DMA copolymer library exhibited slightly larger LCST transitions, presumably due to a slightly higher hydrophilicity over Amor. This study of LCST transitions and copolymer compositions illustrated the usefulness of an automated platform for systematic compositional variation for the analysis of polymer properties.

9.24.7 Ring-Opening Polymerizations Nederberg et al.70 used an automated parallel approach to develop an effective organic catalyst for the ring-opening poly­ merization (ROP). Using a Quest 210 robotic platform, dimethylaminopyridine (DMAP) and 4-pyrrolidinopyridine (PPY) were tested as catalysts for the polymerization of lactide at a variety of different stoichiometries with different initiators, temperatures, and incubation times (Figure 24). Both amines are effective trans-esterification catalysts, but this investigation was the first report of their ability to facilitate ROP. Organocatalyzed poly(lactides) were demonstrated to have defined MWs and low PDIs, and polymerization demonstrated ‘living’ behavior. In addition, the variation of multiple reaction parameters in a systematic fashion identified optimal

conditions for amine-catalyzed ROP that were both mild and selective. The polymerization of 2-substituted 2-oxazolines has the potential to produce a wide array of functional polymers through variation of monomer, initiator, and capping element. The automated, living cationic ROP of 2-substituted 2-oxazo­ line was demonstrated by Hoogenboom et al.71–74 in several reports. Utilizing a Chemspeed ASW2000, researchers investi­ gated the reproducibility and living character of a model system with benzyl bromide (BB) as an initiator and piperidine as a terminating agent.71 Different monomer ([M]) to initiator ([I]) ratios were tested in two distinct experimental setups: (1) 8 parallel reactions on one reactor block and (2) 40 parallel reactions over 5 reactor blocks. Reactions were heated to 80 °C under an argon atmosphere for 24 h before chain-growth termination and were equipped with reflux condensers to mini­ mize solvent evaporation. The resulting polymers were precipitated, washed, and then characterized by NMR, MALDI-TOF, and GPC. Polymers were synthesized reproduci­ bly on this automated platform and yields were comparable to manual synthesis execution up to an MW of 8000 Da (Figure 25). However, a decrease in polymer yield was observed with the increase in higher MW (10 000 Da or more) polymers. The researchers suggest that this loss of poly­ mer may occur during precipitation and transfer of the higher MW polymers. PDIs were narrow and polymers grew linearly with increased monomer to initiator ratios, demonstrating liv­ ing behavior.

477

High-Throughput Approaches

Figure 24 ROP of lactide.

(a) 100

(b)

‘classical’ polymerizations [M]/[I] = 50

Theoretical

10000

2.75

80 2.50

Yield (%)

60

40

2.25

6000

2.00

PDI

Mn (MALDI)

8000

1.75

4000

1.50

20

2000

0

1.25 1.00

0 20

30

40

50

60

70

80

90

100

[M]/[I]

0

10

20

30

40

50

60

70

80

90 100

[M]/[I]

Figure 25 (a) Comparison of automated vs. classical synthesis of poly(2-ethyl-2-oxazolines). (b) MW and PDI versus [M]/[I] for poly(2-ethyl-2­ oxazolines). Adapted from Hoogenboom, R.; Fijten, M. W. M.; Meier, M. A. R.; Schubert, U. S. Macromol. Rapid Commun. 2003, 24 (1), 92–97,4 and reprinted with permission from Wiley.

In a separate report, Hoogenboom et al.72 combinatorially screened four different 2-substituted 2-oxazolines and four different initiators at different monomer to initiator ratios. The monomers 2-methyl-2-oxazoline (MeOx), 2-ethyl-2-oxa­ zoline (EtOx), 2-nonyl-oxazoline (NonOx), and 2-phenyl-2­ oxazoline (PhOx) were combined with the four initiators BB, methyl triflate (MeOTf), methyl tosylate (MeOTs), and MeI to examine the ROP of common monomers and initiators. These 128 different polymerization reactions were monitored at discrete time points by gas chromatography (GC), which allowed for a complete kinetic investigation of these cationic ring-opening reactions in an automated fashion. Insights from these kinetic studies were then adopted into the polymeriza­ tion of random copolymers using these monomers. Greater polymerization rates correlated with decreasing initiator nucleophilicity. For the monomers, the polymerization rate was observed to be MeOx > EtOx ≈ NonOx ≫ PhOx. This kinetic information allowed the researchers to combine two monomers with similar polymerization rates (EtOx and NonOx) to design a truly random copolymer and use mono­ mers with differing rates (MeOx and NonOx) to design polymers with ‘compositional drift’. These studies inspired a third report where Hoogenboom et al.73 used automated methods to perform detailed co­ polymerization studies and establish structure–property relationships of these copolymers. Twenty-seven polymeriza­ tions were performed by taking combinations of MeOx, EtOx, and NonOx in monomer ratios of 0–100%. Monomer conver­ sion was monitored by GC and linear kinetics confirmed the

living polymerization of the monomers. Further analysis of the kinetics of the polymerizations revealed the formation of two classes of copolymers. Random copolymers were observed with EtOx:NonOx monomer combinations, while MeOx:NonOx and MeOx:EtOx combinations yielded gradient copolymers due to the greater reactivity differences between the monomers. These copolymers were then screened to observe how their structural and compositional differences affected their measur­ able properties. The surface energies and thermal properties of the polymers were determined and significant surface energy differences were determined between random and gradient copolymers. Glass transition temperatures, melting tempera­ tures, and heats of fusion displayed only small differences between the two polymer types and changed in a similar fash­ ion within each polymer series. Small differences could be attributed to differences in polymer length rather than mono­ mer distribution. ROP can also be used to generate star-shaped block copo­ lymers in a combinatorial manner.75 Meier et al.75 employed a five-arm star-shaped PEG compound as a macroinitiator for the ROP of ε-caprolactone monomer. Using this strategy, the PEG compound formed the core of the star while the outer shell was comprised of polyesters. Polymerizations were per­ formed on a Chemspeed ASW2000 by mixing monomer and initiator at different ratios and heating to 130 °C. Polymerizations were demonstrated to be reproducible by the low variation in measured MW values in iterative experi­ ments. Moreover, a linear relationship was observed between MWs (calculated by both GPC and NMR) and different [M]/[I]

478

High-Throughput Approaches

ratios. The host–guest properties of these polymers were also analyzed in a 96-well microplate format in an extraction study between water and chloroform. The amount of water-soluble dye methyl orange that was extracted into the chloroform layer in the presence of polymer was recorded by UV/vis absorption. The maximum loading capacity of assayed poly­ mers was determined to be the same for all the polymers tested, revealing that outer shell size had little effect on the extraction capacity of the polymers.

(a)

(c)

(b)

(d)

(e)

9.24.8 Microarray Approaches

(f)

23 21

0

60 9 1 2 7 34 5 6 5 78 9 10 1 2 30% 1 1 13 4 3 mon 1 5 ome 1 16 8 9 1 1 1 0 r 2 21 2 2 23 4 2

70%

11

80 100

mon

15 13

ome

40

r

19 17

20

th ) grow Cell coverage er olym

(% p

To meet the demands of gene expression analysis and the discovery of novel protein ligands from large small-molecule libraries, microarray technology has offered a means to rapidly query a large number of experiments in a fast, cheap, and reliable fashion. The expansion of combinatorial, highthroughput polymer synthesis makes the application of a microarray approach for parallel polymer characterization and for the biological evaluation of polymers ideal. The impact that materials have on their cellular environments is a key aspect of biomaterial-based therapies. To examine both the feasibility and usefulness of the microarray approach in study­ ing polymer effects on cellular behavior, Anderson et al.76 simultaneously characterized over 1700 interactions between human embryonic stem cells (hESCs) and materials using a polymer array. Acrylate-based polymers were evaluated in triplicate on a polymer array where 576 combinations of 25 acrylate, diacrylate, dimethacrylate, and triacrylate monomers were polymerized with 2,2-dimethoxy-2-phenylacetophenone as a light-activated radical initiator.76 Epoxide-functionalized glass slides were first coated with poly(hydroxyethyl methacrylate) (pHEMA) before monomers and radical initiator were depos­ ited on the surface using a PixSys 5500 Cartesian robot for fluid handling. Light-induced polymerization then created rigid polymer spots suitable for screening. The layer of pHEMA was implemented to inhibit cell growth and as a means of immo­ bilizing monomers as they are absorbed onto the surface. The authors could manufacture 20 slides each containing 1728 polymer features in a single day. Embryoid bodies were formed over 6 days and then incubated with arrays to determine the polymer effects on hESC growth and differentiation (Figure 26).76 After incu­ bating the cells on the arrays for 6 days with retinoic acid, the cells were fixed on the arrays and were stained for proteins cytokeratin 7 and vimentin, and a nucleic acid-binding dye (SYTO24). Cytokeratin 7 is a protein indi­ cative of cells in the glandular and transitional epithelia while vimentin is a protein found in mesenchymal-derived cells. While a minority of features displayed an inability for hESCs to attach and spread, the majority of features did allow attachment and spreading and were cytokeratin posi­ tive. Incubation of the arrays with a different cell type, C2C12 embryonic muscle cells, displayed cellular attach­ ment and spreading for nearly all polymer features. Researchers more closely examined the ‘hits’ from these initial arrays by printing 72 replicates of their top 24 polymers. The effect of the presence/absence of retinoic acid on cell behavior at different time intervals could be

Figure 26 Polymer microarrays incubated with hESCs. (a–c) hESCs were incubated with polymer arrays in the presence of retinoic acid for 6 days and then stained for cytokeratin 7 (green) and vimentin (red). (d) Nuclei staining. (e) A cytokeratin 7-positive spot. (f) Cell growth and cell attachment as a function of polymer composition from polymer microarrays. Reprinted from Anderson, D. G.; Levenberg, S.; Langer, R. Nat. Biotechnol. 2004, 22 (7), 863–866,76 with permission from the Nature Publishing Group.

investigated in these secondary arrays. Materials with high levels of differentiation were identified under each of these conditions. In a subsequent report, Anderson et al.77 expanded on this technology by examining the cellular effects of well-character­ ized biodegradable polymers with a range of different cell types. A broad range of polyesters, such as PLGA, and a number of other materials used in biomedical applications were exam­ ined. Blends of these polymers were made in different ratios to create an array of 1152 different experimental samples. These polymers were layered several times on the pHEMA-coated slides in triplicate and dried to create stable polymer features. These 3456-feature arrays were used to understand cell– biomaterial interaction utilizing human mesenchymal stem cells (hMSCs), bovine articular chondrocytes, and neural stem cells. From these experiments, a number of polymeric blends were able to be identified that facilitated cell attachment, spreading, and differentiation of each of the cell types. These experiments demonstrated the ability of polymeric microarray

High-Throughput Approaches

technology to rapidly evaluate material effects of cellular behavior. The parallel characterization of polymer properties is another area where microarray technology can enhance throughput.78,79 Individual sample characterization is a major bottleneck of high-throughput methods, and measurement of mechanical properties of new materials is an important predictor of perfor­ mance in a number of applications. Nanoindentation is a continuous measure of load versus nanometer displacement of a rigid indenter on a material surface that allows for the deter­ mination of material properties of elastic modulus and hardness. Tweedie et al.78 adapted nanoindentation methods to the polymer microarrays designed by Anderson et al.77 The pairwise combinations of 24 acrylate monomers were printed and polymerized on the microarray surface in triplicate, and the 1728 discrete polymer features were analyzed by nanoindenta­ tion.78 The entire array could be analyzed in 24 h in a continuous and automated manner using a MicroMaterials Limited indenter. Replicate measurements displayed low devia­ tion (< 10%) on the triplicate subarrays, demonstrating precision and reproducibility of this method. Accuracy of the method was evaluated by including nanoindentation measure­ ments of the borosilicate glass slide and comparing the determined elastic modulus with known values. Several trends were observed among the measurements of the acrylate-based library. In the majority of the cases, the elastic modulus of copolymers with a significantly larger proportion of one mono­ mer tended to match the modulus of a homopolymer of that monomer alone. Certain monomers were identified that had a large impact on the modulus, even when their concentration in the copolymer was low. Finally, copolymers were identified that had very different mechanical properties from polymers made from their constituent monomers alone. In another demonstration of parallel and high-throughput characterization of a polymer microarray, Urquhart et al.79,80 used XPS, ToF-SIMS, atomic force spectroscopy (AFM), and WCA measurements for surface analysis of arrayed materials. Application of these methods to the same arrayed acrylate-based polymeric library described previously gave a detailed character­ ization of the surface properties for each polymer sample. Each method contributes uniquely to understanding the polymer sur­ face properties: WCA measurements provide the static WCA, which gives information on the wettability of a surface; XPS provides quantitative elemental surface compositions and func­ tional group identification; ToF-SIMS qualitatively analyzes surfaces and gives molecular ion fragment spectra that comple­ ment surface composition information from XPS; AFM was used to study the adsorption of fluorescently labeled proteins to a polymer-arrayed surface. Researchers were able to compile XPS, ToF-SIMS, and WCA data for all arrayed polymers from each of these techniques in a period of just 6 days.79 Interestingly, after measuring the oxy­ gen to carbon ratios for all the polymer samples and comparing them to their WCAs, no correlation was observed for the major­ ity of polymer features except for polymers that contained a hydroxylated monomer. Diacrylate- and triacrylate-containing polymers showed no correlation between oxygen to carbon ratios and WCA measurements. These relationships were indica­ tive of the greater polarity of increased hydroxyl groups relative to backbone polymeric esters and the presence of increased cross-linking having a masking effect on polar functionality.

479

Adhesion forces recorded by a fibronectin-coated AFM probe correlated with fluorescence measurements of protein adhesion on the polymer array, and both methods proved useful in char­ acterizing protein–polymer interactions on a polymer array (Figure 27).80 While only a demonstration, the ability to dis­ cover relationships between surface chemistry and surface properties using this combined multiprong analysis with poly­ meric microarrays is notably powerful.

9.24.9 Other High-Throughput Screening Approaches As a means of expediting the discovery of polymers with antimicrobial properties, Stratton et al.81 utilized biolumines­ cent bacterial reporter strains to track to allow for fast evaluation of bactericidal activity. Polymers with strong anti­ bacterial activity such as quaternized poly(4-vinyl pyridine) (Q-PVP) are attractive because of the comparative advantages over other antimicrobial solutions, in particular Q-PVP’s effi­ cacy against even multidrug-resistant bacteria. However, since Q-PVP displays poor biocompatibility, the discovery of poly­ mers with similar bactericidal properties but with improved biocompatibility would enable a large number of applications. Conventional radical copolymerization of vinyl pyridine (VP), PEGMA and hydroxyethyl methacrylate (HEMA), using AIBN as a radical initiator is one approach that can generate more biocompatible, yet antimicrobial, polymers. The use of geneti­ cally engineered bioluminescent strains of bacteria allows for quantitative, time-sensitive measurements of bacterial growth and lysis. Researchers also applied a quantitative bacteria dynamics model with these data to determine comparable levels of efficacy for different antimicrobial treatments. Copolymerization at different monomer molar ratios gener­ ated a collection of polymers that could be applied onto a 96-well plate. After application of bioluminescent E. coli to the polymer samples, luminescence measurements were taken to measure bacterial density (Figure 28). Analysis of lumines­ cence data together with mathematical modeling enabled the investigators to identify 50% VP and 50% PEGMA copolymer as having optimal antimicrobial activity and selectivity. Zhou et al.82 employed a high-throughput approach for modification of poly(ether sulfone) (PES) membranes as a method to discover new fouling-resistant membrane surfaces. Ninety-six-well filter plates with PES membranes underwent photoinduced graft polymerization (PGP) with 66 vinyl monomers by exposure to UV light (Figure 29). These mono­ mers represented a diverse set of chemical functionalities and were categorized into nine distinct groups: amine, heterocyclic, aromatic, hydroxyl, acid, PEG-derived, hydrophobic methacry­ lates, basic/zwitterionic, and unclassified. Adsorption of a foulant solution (Elliott soil humic acid) was used to evaluate the fouling resistance of the membranes by measuring the hydraulic resistance of the wells before and after solution filtra­ tion. A fouling index was devised in order to assess membrane performance by calculating the increase in resistance in the modified membranes and normalizing against the unmodified membrane control. Examination of fouling indices across the entire collection yielded interesting structure–activity relationships (Figure 30). At least one monomer from each of eight categories performed better than the unmodified control, with only membranes

480

High-Throughput Approaches

(b)

5.5 5.0 4.5

Major monomer 1 21

4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5

Maximum adhension force (nN)

Maximum adhension force (nN)

(a)

0.0

3.0

2.5

2.0

Major monomer 1 21

1.5

1.0

0.5

0.0 0

2

4

6

8

10

12

14

16

18

20

22

24

40

50

60

70

Minor monomer

100

90

WAC (°) (d)

(c)

3.0

1.0 0.9

Major monomer 1 21

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

Maximum adhension force (nN)

Normalized fluorescent intensity

80

2.5

2.0

1.5

1.0

0.5

0.0 0

2

4

6

8

10

12

14

16

18

20

22

24

0.0

Minor monomer

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Normalized fluorescent intensity

Figure 27 (a) Plot displaying the relationship between the measured maximum adhesion force from the fibronectin-coated probe and the 48-polymer library. (b) The relationship between WCA of the 48 polymers and maximum adhesion force. (c) Normalized fluorescence intensity data after incubating polymer arrays with fluorescently labeled fibronectin. (d) The relationship between fluorescence intensity and maximum adhesion force. Adapted from Taylor, M.; Urquhart, A. J.; Anderson, D. G.; et al. Macromol. Rapid Commun. 2008, 29 (15), 1298–1302,80 and reprinted with permission from Wiley.

2.5 2 1.5 1 0.5

3.5 3 2.5 2 1.5 1 0.5

Control PVP-HB

PPEGMA 475 10% VP 90% PEGMA 475 25% VP 75% PEGMA 475 50% VP 50% PEGMA 475 75% VP 25% PEGMA 475

4 Bacteria concentration (relative to t = 0)

Bacteria concentration (relative to t = 0)

3

Control

PVP-HB PPEGMA 1100 25% VP 75% PEGMA 1100 50% VP 50% PEGMA 1100 75% VP 25% PEGMA 1100 90% VP 10% PEGMA 1100

4 Bacteria concentration (relative to t = 0)

Control PVP-HB PPEGMA 300 10% VP 90% PEGMA 300 25% VP 75% PEGMA 300 50% VP 50% PEGMA 300 75% VP 25% PEGMA 300

3.5

3.5 3 2.5 2 1.5 1 0.5

0

0 0

500 1000 1500 2000 2500 3000 3500 4000

0

500

1000 1500 2000 2500 3000 3500

Time (s)

Time (s)

0

0

500 1000 1500 2000 2500 3000 3500 4000 Time (s)

Figure 28 The impact of different VP-PEGMA copolymers on bacterial concentration. Bacterial luminescence was used to quantify bacterial concen­ tration. Adapted from Stratton, T. R.; Garcia, R. E.; Applegate, B. M.; Youngblood, J. P. Biomacromolecules 2009, 10 (5), 1173–1180,81 and reprinted with permission from the American Chemical Society.

modified with aromatic monomer displaying no improvement over the control. The best-performing polymers came from membranes modified with PEG-derived, amine, and basic/ zwitterionic functionalities. Stirred-cell filtration and BSA adsorption of the best-performing membranes confirmed the

results of the initial screen, demonstrating the utility of a high-throughput approach for identifying novel nonfouling surfaces. Transmission electron microscopy (TEM) is a valuable tool for the imaging and characterization of polymeric surfaces.

High-Throughput Approaches

PES o s o o s o

o s o

UV λ = 300 nm

o n

n Monomer

n o n

Grafted polymer chain

UV light

Skin layer

o

o s o

o

481

Pore Base polymer (membrane)

Radical sites

Pore after grafting

Figure 29 Modification of PES membranes with vinyl-containing monomers using the PGP method. Adapted from Zhou, M. Y.; Liu, H. W.; Kilduff, J. E.; et al. Environ. Sci. Technol. 2009, 43 (10), 3865–3871,82 and reprinted with permission from the American Chemical Society.

(a)

(b)

Number of monomers

12

4+

10

3+

8

2+

6

1+

4

1−

2

2− Others

Basic and Zwit

Monomer class

Amine

Acid

PEG

Hydroxy

Aromatic

Hetero ring

HPO MA

0

Monomer class

#

Rating

Zwitterion Other (acrylamide) Amine Zwitterion PEG PEG Amine HPO MAs Amine Zwitterion Acid Amine PEG PEG PEG Hydroxy

60 53 51 61 35 34 55 7 52 59 45 56 33 31 32 32 30 50 63 62 39 29 42

4+ 4+ 3+ 3+ 3+ 3+ 3+ 3+ 3+ 3+ 3+ 2+ 2+ 2+ 2+ 2+ 1+ 1+ 1+ 1+ 1+ 1+ 1+

PEG Acid Basic Basic Hetero ring PEG Acid As-received PES

3− ND

−0.5

0.0

0.5

1.0

1.5

Fouling index (ℜ)

Figure 30 (a) Fouling indices for different monomer classes. The number of monomers in each class with a specific fouling index is shown. (b) Ranking of modified surfaces relative to PES for resistance to natural organic matter (NOM) fouling. Adapted from Zhou, M. Y.; Liu, H. W.; Kilduff, J. E.; et al. Environ. Sci. Technol. 2009, 43 (10), 3865–3871,82 and reprinted with permission from the American Chemical Society.

However, the time-consuming conventional approach to per­ forming TEM is not compatible with the analysis of large combinatorial libraries. To address this discrepancy, Roskov et al.83 devised a new method for harvesting multiple polymer thin films into combinatorial arrays ready for TEM imaging. A combinatorial gradient thickness poly(styrene-b-2-vinyl pyri­ dine) (PS-b-PVP) block copolymer library was laid over a PDMS gasket over a custom-built 48-well ‘basket array’ (Figure 31). Poly(acrylic acid) (PAA) droplets were used as plugs for the holes of the PDMS gasket, and liquid nitrogen freezing of the library caused the thin parts of the thin film in contact with the PAA to differentially contract. ‘Peeling’ of the thin film from the gasket caused film-PAA specimens to be left behind. Subsequent dissolution of PAA with water followed by

draining caused film specimens to be deposited on TEM grids placed on the copper-mesh bottom of the basket array. These film-charged TEM grids allowed for detailed TEM analysis, where variations in film thickness between different samples of the block copolymer library could be easily detected. A number of polystyrene-based block copolymer thin-film libraries were also successfully imaged using this technique, and it also has the potential of increased throughput by fabri­ cation of even larger arrays. Computational modeling and prediction has the potential of greatly facilitating evaluation of large combinatorial libraries.84,85 These approaches have been employed with some success in the pharmaceutical industry for drug discovery, but application of these methods to predict biological

482

High-Throughput Approaches

(a)

1 cm

(b)

PAA droplet

PDMS gasket

25 μm

(c) (d)

TEM grids in mesh baskets

400 μm

50 μm

200 μm

20 μm

Figure 31 (a) Image of the block copolymer thin-film library on a silicon wafer. Film thickness increases from right to left. (b) Image of the PDMS gasket on top of the thin-film library. A poly(acrylic acid) droplet plugs the top-half of the hole. After extraction, disc-shaped specimens are removed from the thin film. (c) Images of the ‘basket array’ with the copper mesh holding the TEM grids, and with the PDMS gasket on top. (d) TEM micrograph of film specimens deposited on TEM grids. Adapted from Roskov, K. E.; Epps, T. H., III; Berry, B. C.; et al. J. Comb. Chem. 2008, 10 (6), 966–973,83 and reprinted with permission from the American Chemical Society.

responses to polymeric materials is still challenging. Kholodovych et al.85 for the first time applied computational modeling and prediction to evaluate a large virtual combina­ torial library of polymeric materials. Quantitative structure– performance relationship (QSPR) models were applied to the virtual screening of a 40 000-member virtual library of polymethacrylates. Seventy-nine polymers were synthesized using RAFT polymerization from a representative sublibrary of 2000 polymethacrylates and used to build the QSPR model for the prediction of cell attachment, cell growth, and fibrinogen adsorption. This model was then applied to predict the out­ comes of these three assays for the remaining library members. Comparison of calculated and measured property values for 50 polymethacrylates chosen from the virtual collection showed good agreement, and these encouraging results are likely to stimulate increased usage of computational methods to aid in the rational design of materials for characterized applications.

References 1. Webster, D. C. Macromol. Chem. Phys. 2008, 209 (3), 237–246. 2. Tuchbreiter, A.; Marquardt, J.; Kappler, B.; et al. Macromol. Rapid Commun. 2003, 24 (1), 47–62. 3. Schmatloch, S.; Meier, M. A. R.; Schubert, U. S. Macromol. Rapid Commun.

2003, 24 (1), 33–46.

4. Hoogenboom, R.; Meier, M. A. R.; Schubert, U. S. Macromol. Rapid Commun.

2003, 24 (1), 16–32.

5. Meier, M. A. R.; Hoogenboom, R.; Schubert, U. S. Macromol. Rapid Commun.

2004, 25 (1), 21–33.

6. Rojas, R.; Harris, N. K.; Piotrowska, K.; Kohn, J. J. Polym. Sci., Polym. Chem.

2009, 47 (1), 49–58.

7. Chisholm, B. J.; Webster, D. C. J. Coat. Technol. Res. 2007, 4 (1), 1–12.

8. Bourke, S. L.; Kohn, J. Adv. Drug Deliv. Rev. 2003, 55 (4), 447–466. 9. Smith, J. R.; Seyda, A.; Weber, N.; et al. Macromol. Rapid Commun. 2004, 25 (1), 127–140. 10. Brocchini, S.; James, K.; Tangpasuthadol, V.; Kohn, J. J. Am. Chem. Soc. 1997, 119 (19), 4553–4554. 11. Brocchini, S.; James, K.; Tangpasuthadol, V.; Kohn, J. J. Biomed. Mater. Res. 1998, 42 (1), 66–75. 12. Kohn, J.; Kauffmann, E. A. B.; Tziampazis, E.; Moghe, P. V. Trans. Sixth World Biomater. Congr. 2000, 1, 84. 13. Belu, A. M.; Brocchini, S.; Kohn, J.; Ratner, B. D. Rapid Commun. Mass Spectrom. 2000, 14 (7), 564–571. 14. Weber, N.; Bolikal, D.; Bourke, S. L.; Kohn, J. J. Biomed. Mater. Res., Part A 2004, 68A (3), 496–503. 15. Effah-Kaufmann, E. A. B.; Kohn, J. Trans. Sixth World Biomater. Congr. 2000, 2, 811. 16. Yang, Y.; Bolikal, D.; Becker, M. L.; et al. Adv. Mater. 2008, 20 (11), 2037–2043. 17. Yang, Y. Y.; Dorsey, S. M.; Becker, M. L.; et al. Biomaterials 2008, 29 (12), 1901–1911. 18. Lynn, D. M.; Langer, R. J. Am. Chem. Soc. 2000, 122 (44), 10761–10768. 19. Akinc, A.; Lynn, D. M.; Anderson, D. G.; Langer, R. J. Am. Chem. Soc. 2003, 125 (18), 5316–5323. 20. Anderson, D. G.; Lynn, D. M.; Langer, R. Angew. Chem. Int. Ed. 2003, 42 (27), 3153–3158. 21. Anderson, D. G.; Peng, W. D.; Akinc, A.; et al. Proc. Natl. Acad. Sci. U.S.A. 2004, 101 (45), 16028–16033. 22. Anderson, D. G.; Akinc, A.; Hossain, N.; Langer, R. Mol. Ther. 2005, 11 (3), 426–434. 23. Green, J. J.; Langer, R.; Anderson, D. G. Acc. Chem. Res. 2008, 41 (6), 749–759. 24. Zugates, G. T.; Tedford, N. C.; Zumbuehl, A.; et al. Bioconjugate Chem. 2007, 18 (6), 1887–1896. 25. Green, J. J.; Zugates, G. T.; Tedford, N. C.; et al. Adv. Mater. 2007, 19 (19), 2836–2842. 26. Anderson, D. G.; Tweedie, C. A.; Hossain, N.; et al. Adv. Mater. 2006, 18 (19), 2614–2618. 27. Thomas, M.; Lu, J. J.; Zhang, C. C.; et al. Pharm. Res. 2007, 24 (8), 1564–1571. 28. Van Vliet, L. D.; Chapman, M. R.; Avenier, F.; et al. ChemBioChem 2008, 9 (12), 1960–1967. 29. Barua, S.; Joshi, A.; Banerjee, A.; et al. Mol. Pharm. 2009, 6 (1), 86–97. 30. Akinc, A.; Goldberg, M.; Qin, J.; et al. Mol. Ther. 2009, 17 (5), 872–879.

High-Throughput Approaches 31. Akinc, A.; Zumbuehl, A.; Goldberg, M.; et al. Nat. Biotechnol. 2008, 26 (5), 561–569. 32. Love, K. T.; Mahon, K. P.; Levins, C. G.; et al. Proc. Natl. Acad. Sci. U.S.A. 2010, 107, 1864–1869. 33. Webster, D. C.; Chisholm, B. J.; Stafslien, S. J. Biofouling 2007, 23 (3–4), 179–192. 34. Potyrailo, R. A.; Chisholm, B. J.; Morris, W. G.; et al. J. Comb. Chem. 2003, 5 (4), 472–478. 35. Potyrailo, R. A.; Chisholm, B. J.; Olson, D. R.; et al. Anal. Chem. 2002, 74 (19), 5105–5111. 36. Potyrailo, R. A.; Ezbiansky, K.; Chisholm, B. J.; et al. J. Comb. Chem. 2005, 7 (2), 190–196. 37. Chisholm, B.; Potyrailo, R.; Cawse, J.; et al. Prog. Org. Coat. 2002, 45 (2–3), 313–321. 38. Casse, F.; Ribeiro, E.; Ekin, A.; et al. Biofouling 2007, 23 (3–4), 267–276. 39. Chisholm, B. J.; Webster, D. C.; Bennett, J. C.; et al. Rev. Sci. Instrum. 2007, 78 (7), 072213. 40. Ekin, A.; Webster, D. C. J. Comb. Chem. 2007, 9 (1), 178–188. 41. Ekin, A.; Webster, D. C.; Daniels, J. W.; et al. J. Coat. Technol. Res. 2007, 4 (4), 435–451. 42. Pieper, R. J.; Ekin, A.; Webster, D. C.; et al. J. Coat. Technol. Res. 2007, 4 (4), 453–461. 43. Stafslien, S.; Daniels, J.; Mayo, B.; et al. Biofouling 2007, 23 (1–2), 45–54. 44. Nasrullah, M. J.; Bahr, J. A.; Gallagher-Lein, C.; et al. J. Coat. Technol. Res. 2009, 6 (1), 1–10. 45. Kugel, A. J.; Jarabek, L. E.; Daniels, J. W.; et al. J. Coat. Technol. Res. 2009, 6 (1), 107–121. 46. Gruter, G. J. M.; Graham, A.; McKay, B.; Gilardoni, F. Macromol. Rapid Commun. 2003, 24 (1), 74–80. 47. Boussie, T. R.; Coutard, C.; Turner, H.; et al. Angew. Chem. Int. Ed. 1998, 37 (23), 3272–3275. 48. Boussie, T. R.; Murphy, V.; Hall, K. A.; et al. Tetrahedron 1999, 55 (39), 11699–11710. 49. Stork, M.; Herrmann, A.; Nemnich, T.; et al. Angew. Chem. Int. Ed. 2000, 39 (23), 4367–4369. 50. Tian, J.; Coates, G. W. Angew. Chem. Int. Ed. 2000, 39 (20), 3626–3629. 51. Boussie, T. R.; Diamond, G. M.; Goh, C.; et al. J. Am. Chem. Soc. 2003, 125 (14), 4306–4317. 52. Mason, A. F.; Coates, G. W. J. Am. Chem. Soc. 2004, 126 (35), 10798–10799. 53. Hinderling, C.; Chen, P. Angew. Chem. Int. Ed. 1999, 38 (15), 2253–2256. 54. Adams, N.; Arts, H. J.; Bolton, P. D.; et al. Chem. Commun. (Camb) 2004, 4, 434–435. 55. Jones, D. J.; Gibson, V. C.; Green, S. M.; Maddox, P. J. Chem. Commun. 2002, 10, 1038–1039. 56. Jones, D. J.; Gibson, V. C.; Green, S. M.; et al. J. Am. Chem. Soc. 2005, 127 (31), 11037–11046. 57. Nasrullah, M. J.; Webster, D. C. Macromol. Chem. Phys. 2009, 210 (8), 640–650. 58. Zhang, H. Q.; Abeln, C. H.; Fijten, M. W. M.; Schubert, U. S. e-Polymers 2006, 8, 1–9. 59. Zhang, H. Q.; Fijten, M. W. M.; Hoogenboom, R.; et al. Macromol. Rapid Commun. 2003, 24 (1), 81–86.

483

60. Zhang, H. Q.; Marin, V.; Fijten, M. W. M.; Schubert, U. S. J. Polym. Sci., Polym. Chem. 2004, 42 (8), 1876–1885. 61. Fijten, M. W. M.; Meier, M. A. R.; Hoogenboom, R.; Schubert, U. S. J. Polym. Sci., Polym. Chem. 2004, 42 (22), 5775–5783. 62. Guerrero-Sanchez, C.; Paulus, R. M.; Fijten, M. W. M.; et al. Appl. Surf. Sci. 2006, 252 (7), 2555–2561. 63. Paulus, R. M.; Fijten, M. W. M.; de la Mar, M. I.; et al. QSAR Comb. Sci. 2005, 24 (7), 863–867. 64. Fournier, D.; Hoogenboom, R.; Thijs, H. M. L.; et al. Macromolecules 2007, 40 (4), 915–920. 65. Chapon, P.; Mignaud, C.; Lizarraga, G.; Destarac, M. Macromol. Rapid Commun. 2003, 24 (1), 87–91. 66. Bosman, A. W.; Heumann, A.; Klaerner, G.; et al. J. Am. Chem. Soc. 2001, 123 (26), 6461–6462. 67. Becer, C. R.; Paulus, R. M.; Hoogenboom, R.; Schubert, U. S. J. Polym. Sci., Polym. Chem. 2006, 44 (21), 6202–6213. 68. Sciannamea, V.; Guerrero-Sanchez, A.; Schubert, U. S.; et al. Polymer 2005, 46 (23), 9632–9641. 69. Eggenhuisen, T. M.; Becer, C. R.; Fijten, M. W. M.; et al. Macromolecules 2008, 41 (14), 5132–5140. 70. Nederberg, F.; Connor, E. F.; Moller, M.; et al. Angew. Chem. Int. Ed. Engl. 2001, 40 (14), 2712–2715. 71. Hoogenboom, R.; Fijten, M. W. M.; Meier, M. A. R.; Schubert, U. S. Macromol. Rapid Commun. 2003, 24 (1), 92–97. 72. Hoogenboom, R.; Fijten, M. W. M.; Schubert, U. S. Abstr. Pap. Am. Chem. Soc. 2004, 227, 287–PMSE. 73. Hoogenboom, R.; Fijten, M. W. M.; Wijnans, S.; et al. J. Comb. Chem. 2006, 8 (2), 145–148. 74. Hoogenboom, R.; Thijs, H. M. L.; Fijten, M. W. M.; Schubert, U. S. J. Polym. Sci., Polym. Chem. 2007, 45 (23), 5371–5379. 75. Meier, M. A. R.; Gohy, J. F.; Fustin, C. A.; Schubert, U. S. J. Am. Chem. Soc. 2004, 126 (37), 11517–11521. 76. Anderson, D. G.; Levenberg, S.; Langer, R. Nat. Biotechnol. 2004, 22 (7), 863–866. 77. Anderson, D. G.; Putnam, D.; Lavik, E. B.; et al. Biomaterials 2005, 26 (23), 4892–4897. 78. Tweedie, C. A.; Anderson, D. G.; Langer, R.; Van Vliet, K. J. Adv. Mater. 2005, 17 (21), 2599–2604. 79. Urquhart, A. J.; Anderson, D. G.; Taylor, M.; et al. Adv. Mater. 2007, 19 (18), 2486–2491. 80. Taylor, M.; Urquhart, A. J.; Anderson, D. G.; et al. Macromol. Rapid Commun. 2008, 29 (15), 1298–1302. 81. Stratton, T. R.; Garcia, R. E.; Applegate, B. M.; Youngblood, J. P. Biomacromolecules 2009, 10 (5), 1173–1180. 82. Zhou, M. Y.; Liu, H. W.; Kilduff, J. E.; et al. Environ. Sci. Technol. 2009, 43 (10), 3865–3871. 83. Roskov, K. E.; Epps, T. H., III; Berry, B. C.; et al. J. Comb. Chem. 2008, 10 (6), 966–973. 84. Holmes, P. F.; Bohrer, M.; Kohn, J. Prog. Polym. Sci. 2008, 33 (8), 787–796. 85. Kholodovych, V.; Gubskaya, A. V.; Bohrer, M.; et al. Polymer 2008, 49 (10), 2435–2439.

484

High-Throughput Approaches

Biographical Sketches Arturo J. Vegas received a BA in biology from Cornell University and a PhD in chemistry from Harvard University. His doctoral studies, which were carried out under the direction of Stuart Schreiber, focused on developing high-throughput methods to synthesize and identify inhibitors and ligands of histone deacetylases. He is currently a postdoctoral associate working in the laboratory of Robert Langer at MIT and with Daniel G. Anderson. His current research focuses on implementing automated combinatorial methods to synthesize and evaluate novel polymers for use in drug delivery.

Daniel G. Anderson is appointed at the David H. Koch Institute for Integrative Cancer Research at the Massachusetts Institute of Technology. He received his PhD in molecular genetics from the University of California at Davis. At MIT, he pioneered the use of robotic methods for the development of smart biomaterials for drug delivery and tissue engineering. He has developed methods that allow rapid synthesis, formulation, analysis, and biological testing of large libraries of biomaterials for use in medical devices, cell therapy, and drug delivery. In particular, the advanced drug delivery systems he has developed provide new methods for nanoparticulate and microparticulate drug delivery, nonviral gene therapy, siRNA delivery, and vaccines. His work has resulted in the publication of over 120 papers, patents, and patent applications. These patents have led to a number of licenses to pharmaceutical, chemical, and biotechnology companies.