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PD) analysis: Survey in Japan pharmaceutical manufacturers association (JPMA)
Drug Metabolism and Pharmacokinetics 34 (2019) 148e154
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Regular Article
Current status and future perspective on preclinical pharmacokinetic and pharmacodynamic (PK/PD) analysis: Survey in Japan pharmaceutical manufacturers association (JPMA) Akihiko Goto a, b, *, Sadahiro Abe a, c, Shoko Koshiba a, d, Koji Yamaguchi a, 1, Nobuo Sato a, e, Yoshikazu Kurahashi f a
Non-Clinical Evaluation Expert Committee, Drug Evaluation Committee, Japan Pharmaceutical Manufacturers Association (JPMA), 2-3-11, Nihombashi-honcho, Chuo-ku, Tokyo, 103-0023, Japan Drug Metabolism and Pharmacokinetics Research Laboratories, Takeda Pharmaceutical Company Limited, 2-26-1, Muraoka-Higashi, Fujisawa, Kanagawa, 251-8555, Japan c Clinical Pharmacology, Clinical Research, Pfizer R&D Japan, Inc., Shinjuku Bunka Quint Building, 3-22-7, Yoyogi, Shibuya-ku, Tokyo, 151-8589, Japan d Pharmacokinetic Research Laboratories, Translational Research Unit, R&D Division, Kyowa Hakko Kirin Co., Ltd., 1188 Shimotogari, Nagaizumi-cho, Sunto-gun, Shizuoka, 411-8731, Japan e Pharmacokinetics and Analysis Laboratory, Pharmaceutical Research Center, Meiji Seika Pharma Co., Ltd., 760 Morooka-cho, Kohoku-ku, Yokohama, 222-8567, Japan f Drug Metabolism & Pharmacokinetics Research Laboratories, Central Pharmaceutical Research Institute, Japan Tobacco Inc., 1-1, Murasaki-cho Takatsuki, Osaka, 569-1125, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 8 August 2018 Received in revised form 24 December 2018 Accepted 15 January 2019 Available online 29 January 2019
Preclinical pharmacokinetic/pharmacodynamic (PK/PD) analysis is an efficient tool for the translational research and proof of mechanism/concept in animals. The questionnaire survey on the practice of preclinical PK/PD analysis was conducted in the member companies of the Japan Pharmaceutical Manufacturers Association (JPMA). According to the survey, 60% of companies conducted preclinical PK/PD analysis and its impact for drug development was different between each of the companies. The frequently analyzed therapeutic areas of preclinical PK/PD analysis were neurology, inflammation and metabolic disease, and those are different from the therapeutic area (infectious disease and oncology) in which PK/PD analysis was considered as effective by the present survey. Many companies which have used preclinical PK/PD analysis for the translation to human PK/PD and for the prediction of dose/ regimen had good communication with other research & development (R&D) departments (e.g. pharmacology/clinical pharmacology). The increase in resources for preclinical PK/PD analysis including education was highly demanded. As a future perspective, the closer collaboration between pharmacokinetics scientists, pharmacologists, toxicologists and clinical pharmacologists and the increase in resources including upskilling and the comprehension of preclinical PK/PD analysis by the project team are considered to lead to efficient contributions to improve the success ratio of drug discovery and development.
Keywords: Preclinical PK/PD Translation Pharmaceutical industry Questionnaire survey Proof of concept Modeling & simulation
© 2019 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.
1. Introduction
* Corresponding author. 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa, 251-8555, Japan. E-mail address: [email protected] (A. Goto). 1 Previous address: Research Division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba, Shizuoka, 412-8513, Japan.
The attrition ratio of clinical trials, especially in Phase 2, is still high although the druggability has recently increased through the advance of drug screening technologies [1,2]. The failure of acquiring proof of concept (POC) in clinical trials leads to damage not only to the pharmaceutical industry but also to patients' hopes. The quantitative and rational approaches were recently recommended by the regulatory agencies for the pharmaceutical industry
https://doi.org/10.1016/j.dmpk.2019.01.004 1347-4367/© 2019 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.
A. Goto et al. / Drug Metabolism and Pharmacokinetics 34 (2019) 148e154
to incorporate into their drug development. Pharmacokinetic/ pharmacodynamic (PK/PD) model analysis is one of them; it is a tool to characterize the relationship between pharmacokinetics and pharmacodynamics quantitatively in a time dependent manner [3,4]. The US Food and Drug Administration (FDA) critical path initiative report noted the importance of modeling and simulation (M&S) in clinical development [5]. The European Medicines Agency (EMA) published guideline on strategies on dose setting for first in human (FIH) studies based on physiologically-based pharmacokinetics model analysis [6]. The Pharmaceuticals and Medical Devices Agency (PMDA) in Japan also published a summary of their own M&S activities [7]. Additionally, a whitepaper on model informed drug discovery and development (MID3) was reported, and PK/PD analysis is well known to be useful in the whole drug developmental stage including clinical trials [8]. A lot of scientific literature has reported good practices of preclinical PK/PD analysis, as shown in Table 1. For example, from the point of view of the translational research (Table 1-I), the integrated information about comparator/competitor is useful for the target setting (effective dose, regimen, steady-state concentration etc.) [9e15], the construction of a PK/PD model of a new molecular entity (NME), and to be applicable to the selection and the optimization of appropriate candidates. Mechanism-based quantitative PK/PD modeling can help to predict clinical outcome and select safe and effective doses and dosing regimens in early clinical development from preclinical data [13,16e22]. Additionally, preclinical PK/ PD modeling is also supportive as proof of mechanism in pharmacological animal models (Table 1-II). The decisions of lead optimization and candidate selection are supported based on in vitro-in vivo (IVIV) correlation [23e25]. PK/PD/Efficacy characterization and evaluation of synergistic efficacy of combination therapy may lead to proof of concept in animal models and appropriate dose setting in pharmacological studies [26e29]. Toxicokinetic/Toxicodynamic (TK/TD) analysis can estimate the mechanism of safety issues. Additionally, PK/PD model analysis could verify the appropriateness of biomarkers for the target engagement and/or transduction [30]. Although there is a lot of scientific literature about PK/PD analysis, only the good practice examples seem to be reported. Additionally it was challenging to understand from this literature and from new drug application (NDA) review materials from 2012 to 2017 whether the pharmaceutical industry practically used
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preclinical PK/PD analysis to improve drug discovery and development through deciding the dosage in the clinical trials. Therefore, the Non-Clinical Evaluation Expert Committee in the Japan Pharmaceutical Manufacturers Association (JPMA) conducted a questionnaire survey and compiled the results to comprehend how preclinical PK/PD analysis is currently used at research-based pharmaceutical companies in Japan. 2. Materials and methods The present questionnaire survey was sent to 61 company members of JPMA using the commercial online survey software Qooker (SoftAgency Co., Ltd., Japan). The survey questions included single/multiple choice, Yes/No and free text. The survey consisted of 37 questions aimed to gather information in 6 different areas: “Background”, “Experience”, “Policy and strategy”, “Organization and collaboration”, “Usefulness and purpose” and “Future perspective”. The collection of responses occurred in a period of about 1-month (July to August 2017). All responses to the questionnaire were kept anonymous. Data analysis was conducted using Microsoft Excel (Microsoft Corporation, USA). In addition to simple answer counting, the stratified analysis was also conducted and gave potential reasons as to why certain trends were observed. 3. Results The responses were obtained from 53 companies (response rate: 87%). The majority (66%) of respondents were from companies with 5000 employees and 77% of respondents were Japanese companies. In most companies (97%), the members in the drug metabolism and pharmacokinetics (DMPK) department conducted preclinical PK/PD analyses. Then clinical pharmacology (22%), preclinical pharmacology (19%) and pharmacometrics/Model & Simulation (16%) departments followed (supplemental table S1). All survey questionnaires and responses are presented in the supplemental file. 4. Discussion PK/PD analysis has recently played a greater and more central role in drug discovery and development and its importance is well recognized as an efficient tool for the translational research and proof of mechanism/concept in animals (Table 1). As for the
Table 1 Good practice of preclinical PK/PD analysis based on literature. Item Description I. Translation to clinical study setting from preclinical analysis Target setting (effective dose, regimen, steady-state level etc.) of NME by utilizing clinical information of Integration of comparator/ comparator/competitor with some assumptions (no inter-species differences, correction of in vitro competitor information to potency, etc.). The constructed PK/PD model and target setting for NME can be applicable to selection translation of preclinical and optimization of subsequent candidates. findings of new molecular entity (NME) Mechanism-based quantitative PK/PD modeling can help to predict clinical outcome and select safe and PK/PD modeling-based effective doses and dosing regimens in early clinical development. prediction of clinical outcome/response from preclinical findings II. Support of preclinical proof of concept. IVIV correlation Proof of mechanism of action in preclinical species by confirming the correlation between in vitro (binding or efficiency) and in vivo (target engagement or phenotypic effect). M&S approach is effective to solve the hysteresis and conduct mechanism-based analysis (distinguish the binding and signal transduction). PK/PD/Efficacy or TK/TD Characterize time-dependent PK/PD or TK/TD relationship with quantitative manner. The modeling characterization proves the hypothesis and identifies the unexpected mechanism. The hypothetical scenario can be simulated by the constructed model and it can support candidate optimization. Combination therapy Verify the concept of combination therapy in animals. M&S approach can investigate the additivity with quantitative manner. Various scenarios of dose regimen can be simulated using the developed model. Biomarker for PD Verify the hypothesis that the biomarkers may be useful in pharmacological response. The appropriate biomarker can lead to elucidate the mechanism of action.
Reference [9e15]
[13,16e22]
[23e25]
[26,27]
[28,29] [30]
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translational research, PK/PD models constructed based on the integration of clinical information of comparator/competitor [9e15] and mechanism-based quantitative models [13,16e22] are useful for the prediction of clinical outcomes and the setting of safe and effective doses and dosing regimens in early clinical developments of new molecular entities (NME). And as for the support of preclinical proof of concept, PK/PD M&S approachs are useful for verifying various hypotheses, such as in vitro (binding or efficacy) and in vivo (target engagement or phenotypic effect) (IVIV) correlation [23e25], time-dependent PK/PD or TK/TD relationships [26,27], concept of combination therapy [28,29], and appropriateness of PD biomarkers [30]. However, it is difficult to identify the real practice/application of preclinical PK/PD analysis in pharmaceutical companies from the NDA review documents and scientific literature. The questionnaire survey was conducted and the results were compiled to comprehend how preclinical PK/PD analysis is currently used. Concerning the experience of preclinical PK/PD analysis, 60% of the respondents have experience of conducting preclinical PK/PD analysis, the experienced ratio was higher in the companies with >5000 employees than those with 5000 (Fig. 1A). The numbers of respondents who have experience of conducting preclinical PK/PD analyses and to reflect the PK/PD analysis results to the clinical studies (hereafter called as “PK/PD Experienced Company” and “Translational Company”, respectively) were almost the same between companies with >5000 employees and those with 5000 employees (15 vs 17 or 11 vs 12 companies, Fig. 1A or 1B, respectively). A respondent who has NO experience of reflecting PK/PD analysis results to the clinical studies is referred to as a “No Translational Company”. A respondent who has never conducted PK/PD analysis is referred to as a “PK/PD Inexperienced Company”. Almost all Translational Companies reflected preclinical PK/PD analysis results to Phase 1- study protocols and about half of them also reflected preclinical PK/PD analysis results to POC study protocols (Fig. 1C). The more frequently analyzed therapeutic areas of preclinical PK/PD analysis were neurology, inflammation and metabolic disorders and those were different from the therapeutic areas (infectious disease and oncology) in which PK/PD analysis was considered as effective in the present survey (Fig. 2A and B). However, in the previous survey from 22 pharmaceutical companies conducted by IQ consortium, the therapeutic area that preclinical PK/PD modeling had given the most impact to was oncology [31]. The similar trend showing high expectation of translation of preclinical PK/PD analysis in oncology was observed in the literature reporting good practices of preclinical PK/PD analysis (Table 1). It is not difficult to imagine the importance of preclinical PK/PD analysis, because the patients are enrolled into Phase 1 studies in oncology and so preclinical PK/PD analysis is essential to set the dosing range. The present survey respondents considered that preclinical PK/PD analysis was effective in the oncology area, but the actual implementation ratio was not so high. Although the reason for the difference between the two surveys is unclear, the difference in the constitution of respondents might have some impact on the difference, for example, the majority of the present survey respondents were Japanese companies (77%). In the present survey, the focused therapeutic areas of respondent company is unknown. The analyzed therapeutic areas could highly depend on the focused therapeutic areas in each of the pharmaceutical companies. Therefore, it could be also one of the reason for the low implementation ratio preclinical PK/PD analysis for oncology and infectious disease comparing to effectiveness ratio. In metabolic diseases and infectious diseases, the results by preclinical PK/PD analysis was well reflected to the clinical study
A)
PK/PD nced Inexperienced ny y Company (40%))
≤ 5000 > 5000 PK/PD Experien Experienced Company (60%)
B)
No Translational ational y (28% %) Company (28%) ≤ 5000 > 5000 Translational Compa Company (72%)
C) 91%
Phase 1 POC
52%
Others*
9% 0
10
20
Number of respondent Fig. 1. Experience of preclinical PK/PD analysis and its reflection to the protocol of clinical studies. A) experience of preclinical PK/PD analysis in all respondents, B) reflection of PK/PD analysis to the clinical study protocol in PK/PD Experienced Company, C) clinical study stages designed based on PK/PD analysis in Translational Company. PK/PD Inexperienced Company: a company having no experience of conducting preclinical PK/PD analysis, PK/PD Experienced Company: a company having experience of conducting preclinical PK/PD analysis and consisting of Translational and No Translational Companies. No Translational Company: a company having experience of conducting preclinical PK/PD analysis but no experience to reflect it in clinical studies, Translational Company: a company having experience of reflecting preclinical PK/PD analysis in clinical studies, POC: Proof of concept. Inner pie chart in A) and B) indicates the company size (the number of employees). *:concomitant medication in clinical studies, etc.
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A) TA: analyzed by preclinical PK/PD analysis Infectious disease
C) TA: analyzed using same PD markers or correlated with preclinical data
41%
Oncology
Oncology
41%
Neurology
63%
Inflammation
63%
Metabolic disorders
63% 34%
Others 0
5 10 15 Number of respondent
57%
Infectious disease
53%
Cardiovascular
43%
Cardiovascular
32%
Neurology
43%
Inflammation
32%
Metabolic disorders
64%
Others
20
21% 0
B) TA: effectively analyzed by preclinical PK/PD analysis Infectious disease
71% 71%
Oncology Cardiovascular
45% 65% 52%
Metabolic disorders 35% 0
5 10 15 Number of respondent
Infectious disease
61% 35%
Cardiovascular
30% 48% 39%
Inflammation Metabolic disorders
20
20
D) TA: reflecting the result of preclinical PK/PD analysis to clinical data
Neurology 61%
Others
5 10 15 Number of respondent
Oncology
Neurology Inflammation
151
70% 22%
Others 0
5 10 15 Number of respondent
20
Fig. 2. Therapeutic area (TA) and application degree of preclinical PK/PD analysis. A) TA conducted preclinical PK/PD analysis, B) TA effectively conducted preclinical PK/PD analysis, C) TA conducted clinical PK/PD analysis using the same PD markers or correlated with preclinical data, D) TA reflected the result of preclinical PK/PD analysis to clinical data.
planning and it might be caused by the availability of common PD makers both in preclinical and clinical studies (Fig. 2C and D). Ninety-five percent of the Translational Companies responded that preclinical PK/PD analysis was influential or partially influential on the internal decision making of drug discovery and development (Fig. 3). On the other hand, the same responses were indicated by only 55% of the No Translational Companies. This significant impact on decision making in Translational Companies was consistent with the reflection of preclinical PK/PD analysis on the clinical study planning. In other words, the successful experience of translation might evolve the recognition of the importance of preclinical PK/PD analysis. The respondents' satisfactory degree of collaboration with pharmacologists and clinical pharmacologists was much higher in Translational Companies than those with No Translational Companies (Fig. 4). As described above, most respondents were preclinical DMPK members, and so the collaboration with their pharmacologists was considered to be most important point element for feasibility and appropriateness of PD evaluation. The collaboration with the clinical pharmacologists could be effective to translation and clinical dose prediction. It was suggested that the usefulness of preclinical PK/PD analysis to clinical study planning heavily depended on the collaboration with pharmacology and clinical pharmacology departments. Namely, the usefulness and impact of preclinical PK/PD analyses might be improved by enhancing collaboration with related departments. Even in Translational Companies, there is room for improvement of the satisfactory degree of collaboration with pharmacology and clinical pharmacology, suggesting that the closer collaboration could lead more efficient application of preclinical PK/PD analysis. Additionally, collaboration with toxicologist could be also important in case of TK/TD analysis, even though current questionnaire did not ask about collaboration with toxicologists. For the future perspective, the increase of resources, especially personnel, was highly demanded (Fig. 5). “Education/training” and “Collaboration with other departments” were the most common demands for the major necessities for conducting efficient preclinical PK/PD analyses. The collaboration with other departments is required mostly by Translational Companies followed by No
Translational Companies and PK/PD Inexperienced Companies. It was suggested that the importance of collaboration was more strongly recognized through their experiences of preclinical PK/PD
A) Translational Company (23 companies)
Reference level or not influence (4%)
Influential (43%) Partially influence (52%)
B) No Translational Company (9 companies) Lack of experience or unknown (33%)
Reference level or not influence (11%)
Influential (11%)
Partially influential (44%)
Fig. 3. The impact of the results of preclinical PK/PD analysis on internal decision making. A) Translational Company (23 companies), B) No Translational Company (9 companies).
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(78%), “For the pharmacology studies (70%). The comprehensive analysis of these high ratio purposes could lead the best practice as described in Table 1. These differences in the purpose and usefulness between Translational and No Translational Companies might be the key points for the efficient use of the PK/PD analysis goals. The responses to other questionnaires were listed in Supplemental Table S1. We listed the discussion and interpretation for highly important questions as below.
Fig. 4. Satisfactory degrees of collaboration with other departments for PK/PD analysis. A) With pharmacology departments, B) With clinical pharmacology departments. The percentages in the red boxes represent the ratios of answers “Very satisfied”, “Sufficient” and “So-so” to the total responses.
analysis. The Translational Companies considered that increasing resources for the preclinical PK/PD analysis could lead to efficient drug development (Fig. 6). In the PK/PD Inexperienced Companies and No Translational Companies, the impact on and the applicability of preclinical PK/PD analysis to drug development might be considered as relatively limited. The expected purpose and usefulness of preclinical PK/PD analysis was also investigated (Fig. 7). The leading answer was “relationship of PK and efficacy (78%)” in No Translational Companies, but the ratio of other answers was less than 50%. On the other hand, Translational Companies showed higher ratios in the following answers: “Relationship of PK and efficacy (91%)”, “IVIV relationship of efficacy (87%)”, “For best clinical dosage regimens
Question I-5 and II-3-1: There were some differences on the affiliation between responders and actual PK/PD analysts. It might lead to some bias on the answers for the questionnaire. Question II-4, II-5 and III-9: The responses that the preclinical PK/PD analysis could be applied to more than 70% of their developmental compounds reached only 12 companies out of 32. A comparable number of companies conducted preclinical PK/PD analysis at lead optimization stage and after candidate selection, even though earlier application could be more efficient. The most probable reasons of less and late PK/PD analysis application were suggested absence of appropriate PD markers and the lack of M&S experts. It was suggested that the discovery of PD markers at the early stage could be the key solution. Question II-6: Compared to PK/PD analysis, less companies have experience of TK/TD analysis. The possible reasons might be difficulty of analysis due to non-numerical evaluation of toxicity and unclear detailed mechanism by lack of in vitro evaluation system. The more quantitative safety assessment might enable TK/TD analysis in the future. Question III-1: It was considered that many companies tended to adopt a simple model at first to evaluate the PK/PD relationship. Question III-2: Each type of model was used evenly. It was suggested that an appropriate model was selected based on the pharmacological mechanism or the character of the drugs. Question III-4: Preclinical PK/PD analysis was applied to both small molecule drugs and biological drugs. The response might depend on the focused therapeutic area in the respondent companies, but it was suggested that the preclinical PK/PD analysis is useful to development irrespective of modalities of drugs. Question III-10: Many companies tried to update the PK/PD model after the preclinical stage when they could find a proper PD biomarker or the model was applied to backup candidates. It was considered that they tended to increase the prediction accuracy by updating the model. It might also depend on the timing of initiation of analysis (II-5). Question V-3: Many companies used (or plan to use) the preclinical PK/PD analysis not only for internal decisions, but also
Fig. 5. Expected vision of resource and activities for promoting preclinical PK/PD analysis. A) Preferable resource number for preclinical PK/PD analysis in the future, B) Expected necessary activities to enhance efficient preclinical PK/PD analysis.
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A) PK/PD Inexperienced Company
Other (30%) For supporting to MOA (25%)
B) No Translational Company Other (13%)
For efficient drug development (45%)
For supporting to MOA (38%)
For efficient drug development (50%)
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C) Translational Company Only prediction of human PK (9%)
Other (4%)
For supporting to MOA (9%)
For efficient drug development (78%)
Fig. 6. Reasons for the response to the question about resource necessity to advance PK/PD analysis in Fig. 5. A) PK/PD Inexperienced Company, B) No Translational Company, C) Translational Company.
regulatory application. Preclinical PK/PD analysis may increase the importance during drug discovery and development. Question VI-4: Only 10 companies out of 32 have used quantitative systems pharmacology (QSP). In the IQ survey, over 90% of companies have had experience [31]. QSP is likely to be expanded in the future as result of the IQ consortium survey about preclinical QSP [32].
A) No Translational Company For pharmacology studies Compound optimization Relationship of PK and efficacy
The present analysis of survey results revealed that the importance of preclinical PK/PD analysis was well recognized among pharmaceutical companies. However, there might be some obstacles against making good use of preclinical PK/PD analysis for more efficient drug discovery and development. Especially, the resource increase in education/training and the collaboration between related departments were suggested to be highly important. Based on the results of the present survey, the authors propose the workflow for the efficient use of preclinical PK/PD analysis as below.
22% 33% 78%
Mode of Action
22%
IVIV relationship of efficacy For optimal Clinical study designs For best Clinical dosage regimens
44% 0%
11% 0
5
10
Number of respondent
B) Translational Company For pharmacology studies Compound optimization Relationship of PK and efficacy
70% 61% 91%
Mode of Action
39%
IVIV relationship of efficacy For optimal Clinical study designs For best Clinical dosage regimens
87% 57% 78% 0
10 Number of respondent
Question VI-5-1 and VI-5-2: Only one-fifth (or about 20%) of the respondent companies thought that the guideline/guidance about PK/PD analysis was necessary. The reasons why many companies did not need it were 1) not preferable to follow, 2) difficult to develop guidelines and 3) no opportunity to follow because the PK/PD analysis result is only used for internal decision making. The requests of preclinical guidelines/guidance might increase if PK/PD analyses were more available and improved to be more effective.
1. Pharmacokinetic experts' involvement in setting the appropriate experimental conditions of pharmacological studies for PK/PD analysis. It is important for pharmacokinetic experts to encourage collaboration especially with pharmacologists in the early stage of drug discovery for identifying the PD markers. 2. Evaluation of the in vitro/in vivo relationship between drug efficacy and drug concentration in plasma or target site quantitatively and time dependently. 3. Translation of the results of preclinical PK/PD analyses to clinical study planning through the discussion with clinical pharmacologists for the setting of the dosage regimens which are expected to show good efficacy and avoid unexpected side effects. 4. After the confirmation and validation of PK/PD model in the clinical study and biological information and/or knowledge accumulation, reverse translation of the model (potentially QSP model) to preclinical research could be efficient for subsequent drug research and development. The proposed workflow would contribute to efficient drug discovery and development and then be sure to lead to an increased success rate of the clinical studies. The further effort for the preclinical PK/PD analysis would be mandatory to get the required resources and skills to expand the use of preclinical PK/PD analysis.
20
Fig. 7. Expected purpose and usefulness for PK/PD analysis. A) No Translational Company, B) Translational Company.
Conflicts of interest We have the following financial relationships to disclose for our manuscript contents.
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Employees: Akihiko Goto (Takeda Pharmaceutical Company Limited), Sadahiro Abe (Pfizer Japan, Inc.), Shoko Koshiba (Kyowa Hakko Kirin Co., Ltd.), Koji Yamaguchi (Chugai Pharmaceutical Co., Ltd., (retired)), Nobuo Sato (Meiji Seika Pharma Co., Ltd.), Yoshikazu Kurahashi (Japan Tobacco Inc.) Declaration of interest Employees of affiliation companies. Author contributions All authors prepared the questionnaire survey, analyzed the results and prepared and reviewed this manuscript. The authors equally contributed to the present work. Acknowledgement The authors gratefully thank the members of the Non-Clinical Evaluation Expert Committee, Drug Evaluation Committee, JPMA for their response to the survey. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.dmpk.2019.01.004. References [1] Paul SM, Mytelka DS, Dunwiddie CT, Persinger CC, Munos BH, Lindborg SR, et al. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat Rev Drug Discov 2010;9(3):203e14. [2] Schuhmacher A, Gassmann O, Hinder M. Changing R&D models in researchbased pharmaceutical companies. J Transl Med 2016;14(1):105. [3] Lave T, Caruso A, Parrott N, Walz A. Translational PK/PD modeling to increase probability of success in drug discovery and early development. Drug Discov Today Technol 2016;21e22:27e34. [4] Ploeger BA, van der Graaf PH, Danhof M. Incorporating receptor theory in mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling. Drug Metab Pharmacokinet 2009;24(1):3e15. [5] Kimko H, Pinheiro J. Model-based clinical drug development in the past, present and future: a commentary. Br J Clin Pharmacol 2015;79(1):108e16. [6] EMEA/CHMP. Guideline on strategies to identify and mitigate risks for first-inhuman and early clinical trials with investigational medicinal products. 2017. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_ guideline/2017/07/WC500232186.pdf. [7] Sato M, Ochiai Y, Kijima S, Nagai N, Ando Y, Shikano M, et al. Quantitative modeling and simulation in PMDA: a Japanese regulatory perspective. CPT Pharmacometrics Syst Pharmacol 2017;6(7):413e5. [8] Manolis E, Brogren J, Cole S, Hay JL, Nordmark A, Karlsson KE, et al. Commentary on the MID3 good practices paper. CPT Pharmacometrics Syst Pharmacol 2017;6(7):416e7. [9] Kreilgaard M, Smith DG, Brennum LT, Sanchez C. Prediction of clinical response based on pharmacokinetic/pharmacodynamic models of 5hydroxytryptamine reuptake inhibitors in mice. Br J Pharmacol 2008;155(2):276e84. [10] Melhem M. Translation of central nervous system occupancy from animal models: application of pharmacokinetic/pharmacodynamic modeling. J Pharmacol Exp Therapeut 2013;347(1):2e6. [11] Maurer TS, Ghosh A, Haddish-Berhane N, Sawant-Basak A, Boustany-Kari CM, She L, et al. Pharmacodynamic model of sodium-glucose transporter 2 (SGLT2) inhibition: implications for quantitative translational pharmacology. AAPS J 2011;13(4):576e84. [12] Liu D, Ma X, Liu Y, Zhou H, Shi C, Wu F, et al. Quantitative prediction of human pharmacokinetics and pharmacodynamics of imigliptin, a novel DPP-4 inhibitor, using allometric scaling, IVIVE and PK/PD modeling methods. Eur J Pharm Sci 2016;89:73e82.
[13] Haddish-Berhane N, Shah DK, Ma D, Leal M, Gerber HP, Sapra P, et al. On translation of antibody drug conjugates efficacy from mouse experimental tumors to the clinic: a PK/PD approach. J Pharmacokinet Pharmacodyn 2013;40(5):557e71. [14] Ankrom W, Wood HB, Xu J, Geissler W, Bateman T, Chatterjee MS, et al. Preclinical and translational evaluation of coagulation factor IXa as a novel therapeutic target. Pharmacol Res Perspect 2016;4(1), e00207. [15] Shah DK, King LE, Han X, Wentland JA, Zhang Y, Lucas J, et al. A priori prediction of tumor payload concentrations: preclinical case study with an auristatin-based anti-5T4 antibody-drug conjugate. AAPS J 2014;16(3): 452e63. [16] Yamazaki S. Translational pharmacokinetic-pharmacodynamic modeling from nonclinical to clinical development: a case study of anticancer drug, crizotinib. AAPS J 2013;15(2):354e66. [17] Vugmeyster Y, Rohde C, Perreault M, Gimeno RE, Singh P. Agonistic TAM-163 antibody targeting tyrosine kinase receptor-B: applying mechanistic modeling to enable preclinical to clinical translation and guide clinical trial design. mAbs 2013;5(3):373e83. [18] Shah DK, Haddish-Berhane N, Betts A. Bench to bedside translation of antibody drug conjugates using a multiscale mechanistic PK/PD model: a case study with brentuximab-vedotin. J Pharmacokinet Pharmacodyn 2012;39(6): 643e59. [19] Wong H, Vernillet L, Peterson A, Ware JA, Lee L, Martini JF, et al. Bridging the gap between preclinical and clinical studies using pharmacokineticpharmacodynamic modeling: an analysis of GDC-0973, a MEK inhibitor. Clin Canc Res 2012;18(11):3090e9. [20] Tanaka C, O'Reilly T, Kovarik JM, Shand N, Hazell K, Judson I, et al. Identifying optimal biologic doses of everolimus (RAD001) in patients with cancer based on the modeling of preclinical and clinical pharmacokinetic and pharmacodynamic data. J Clin Oncol 2008;26(10):1596e602. [21] Betts AM, Haddish-Berhane N, Tolsma J, Jasper P, King LE, Sun Y, et al. Preclinical to clinical translation of antibody-drug conjugates using PK/PD modeling: a retrospective analysis of inotuzumab ozogamicin. AAPS J 2016;18(5):1101e16. [22] Lindauer A, Valiathan CR, Mehta K, Sriram V, de Greef R, Elassaiss-Schaap J, et al. Translational pharmacokinetic/pharmacodynamic modeling of tumor growth inhibition supports dose-range selection of the anti-PD-1 antibody pembrolizumab. CPT Pharmacometrics Syst Pharmacol 2017;6(1):11e20. [23] Kalvass JC, Olson ER, Cassidy MP, Selley DE, Pollack GM. Pharmacokinetics and pharmacodynamics of seven opioids in P-glycoprotein-competent mice: assessment of unbound brain EC50,u and correlation of in vitro, preclinical, and clinical data. J Pharmacol Exp Therapeut 2007;323(1):346e55. [24] Visser SA, Wolters FL, Gubbens-Stibbe JM, Tukker E, Van Der Graaf PH, Peletier LA, et al. Mechanism-based pharmacokinetic/pharmacodynamic modeling of the electroencephalogram effects of GABAA receptor modulators: in vitro-in vivo correlations. J Pharmacol Exp Therapeut 2003;304(1):88e101. [25] Li CS, Zhang L, Haske T, Dounay A, Gray D, Barta N, et al. Mechanism-based pharmacokinetic/pharmacodynamic modeling of rat prefrontal cortical dopamine response to dual acting norepinephrine reuptake inhibitor and 5HT1A partial agonist. AAPS J 2012;14(2):365e76. [26] Shimizu R, Kitade M, Kobayashi T, Hori S, Watanabe A. Pharmacokineticpharmacodynamic modeling for reduction of hepatic apolipoprotein B mRNA and plasma total cholesterol after administration of antisense oligonucleotide in mice. J Pharmacokinet Pharmacodyn 2015;42(1):67e77. [27] Jiang XL, Shen HW, Mager DE, Schmidt S, Yu AM. Development of a mechanism-based pharmacokinetic/pharmacodynamic model to characterize the thermoregulatory effects of serotonergic drugs in mice. Acta Pharm Sin B 2016;6(5):492e503. [28] Rocchetti M, Del Bene F, Germani M, Fiorentini F, Poggesi I, Pesenti E, et al. Testing additivity of anticancer agents in pre-clinical studies: a PK/PD modelling approach. Eur J Cancer 2009;45(18):3336e46. [29] Li JY, Ren YP, Yuan Y, Ji SM, Zhou SP, Wang LJ, et al. Preclinical PK/PD model for combined administration of erlotinib and sunitinib in the treatment of A549 human NSCLC xenograft mice. Acta Pharmacol Sin 2016;37(7):930e40. [30] Swierczek A, Wyska E, Bas S, Woyciechowska M, Mlynarski J. PK/PD studies on non-selective PDE inhibitors in rats using cAMP as a marker of pharmacological response. Naunyn-Schmiedeberg's Arch Pharmacol 2017;390(10): 1047e59. [31] Schuck E, Bohnert T, Chakravarty A, Damian-Iordache V, Gibson C, Hsu CP, et al. Preclinical pharmacokinetic/pharmacodynamic modeling and simulation in the pharmaceutical industry: an IQ consortium survey examining the current landscape. AAPS J 2015;17(2):462e73. [32] Nijsen M, Wu F, Bansal L, Bradshaw-Pierce E, Chan JR, Liederer BM, et al. Preclinical QSP modeling in the pharmaceutical industry: an IQ consortium survey examining the current landscape. CPT Pharmacometrics Syst Pharmacol 2018;7(3):135e46.
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Drug Metabolism and Pharmacokinetics journal homepage: http://www.journals.elsevier.com/drug-metabolism-andpharmacokinetics
Regular Article
Current status and future perspective on preclinical pharmacokinetic and pharmacodynamic (PK/PD) analysis: Survey in Japan pharmaceutical manufacturers association (JPMA) Akihiko Goto a, b, *, Sadahiro Abe a, c, Shoko Koshiba a, d, Koji Yamaguchi a, 1, Nobuo Sato a, e, Yoshikazu Kurahashi f a
Non-Clinical Evaluation Expert Committee, Drug Evaluation Committee, Japan Pharmaceutical Manufacturers Association (JPMA), 2-3-11, Nihombashi-honcho, Chuo-ku, Tokyo, 103-0023, Japan Drug Metabolism and Pharmacokinetics Research Laboratories, Takeda Pharmaceutical Company Limited, 2-26-1, Muraoka-Higashi, Fujisawa, Kanagawa, 251-8555, Japan c Clinical Pharmacology, Clinical Research, Pfizer R&D Japan, Inc., Shinjuku Bunka Quint Building, 3-22-7, Yoyogi, Shibuya-ku, Tokyo, 151-8589, Japan d Pharmacokinetic Research Laboratories, Translational Research Unit, R&D Division, Kyowa Hakko Kirin Co., Ltd., 1188 Shimotogari, Nagaizumi-cho, Sunto-gun, Shizuoka, 411-8731, Japan e Pharmacokinetics and Analysis Laboratory, Pharmaceutical Research Center, Meiji Seika Pharma Co., Ltd., 760 Morooka-cho, Kohoku-ku, Yokohama, 222-8567, Japan f Drug Metabolism & Pharmacokinetics Research Laboratories, Central Pharmaceutical Research Institute, Japan Tobacco Inc., 1-1, Murasaki-cho Takatsuki, Osaka, 569-1125, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 8 August 2018 Received in revised form 24 December 2018 Accepted 15 January 2019 Available online 29 January 2019
Preclinical pharmacokinetic/pharmacodynamic (PK/PD) analysis is an efficient tool for the translational research and proof of mechanism/concept in animals. The questionnaire survey on the practice of preclinical PK/PD analysis was conducted in the member companies of the Japan Pharmaceutical Manufacturers Association (JPMA). According to the survey, 60% of companies conducted preclinical PK/PD analysis and its impact for drug development was different between each of the companies. The frequently analyzed therapeutic areas of preclinical PK/PD analysis were neurology, inflammation and metabolic disease, and those are different from the therapeutic area (infectious disease and oncology) in which PK/PD analysis was considered as effective by the present survey. Many companies which have used preclinical PK/PD analysis for the translation to human PK/PD and for the prediction of dose/ regimen had good communication with other research & development (R&D) departments (e.g. pharmacology/clinical pharmacology). The increase in resources for preclinical PK/PD analysis including education was highly demanded. As a future perspective, the closer collaboration between pharmacokinetics scientists, pharmacologists, toxicologists and clinical pharmacologists and the increase in resources including upskilling and the comprehension of preclinical PK/PD analysis by the project team are considered to lead to efficient contributions to improve the success ratio of drug discovery and development.
Keywords: Preclinical PK/PD Translation Pharmaceutical industry Questionnaire survey Proof of concept Modeling & simulation
© 2019 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.
1. Introduction
* Corresponding author. 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa, 251-8555, Japan. E-mail address: [email protected] (A. Goto). 1 Previous address: Research Division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba, Shizuoka, 412-8513, Japan.
The attrition ratio of clinical trials, especially in Phase 2, is still high although the druggability has recently increased through the advance of drug screening technologies [1,2]. The failure of acquiring proof of concept (POC) in clinical trials leads to damage not only to the pharmaceutical industry but also to patients' hopes. The quantitative and rational approaches were recently recommended by the regulatory agencies for the pharmaceutical industry
https://doi.org/10.1016/j.dmpk.2019.01.004 1347-4367/© 2019 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.
A. Goto et al. / Drug Metabolism and Pharmacokinetics 34 (2019) 148e154
to incorporate into their drug development. Pharmacokinetic/ pharmacodynamic (PK/PD) model analysis is one of them; it is a tool to characterize the relationship between pharmacokinetics and pharmacodynamics quantitatively in a time dependent manner [3,4]. The US Food and Drug Administration (FDA) critical path initiative report noted the importance of modeling and simulation (M&S) in clinical development [5]. The European Medicines Agency (EMA) published guideline on strategies on dose setting for first in human (FIH) studies based on physiologically-based pharmacokinetics model analysis [6]. The Pharmaceuticals and Medical Devices Agency (PMDA) in Japan also published a summary of their own M&S activities [7]. Additionally, a whitepaper on model informed drug discovery and development (MID3) was reported, and PK/PD analysis is well known to be useful in the whole drug developmental stage including clinical trials [8]. A lot of scientific literature has reported good practices of preclinical PK/PD analysis, as shown in Table 1. For example, from the point of view of the translational research (Table 1-I), the integrated information about comparator/competitor is useful for the target setting (effective dose, regimen, steady-state concentration etc.) [9e15], the construction of a PK/PD model of a new molecular entity (NME), and to be applicable to the selection and the optimization of appropriate candidates. Mechanism-based quantitative PK/PD modeling can help to predict clinical outcome and select safe and effective doses and dosing regimens in early clinical development from preclinical data [13,16e22]. Additionally, preclinical PK/ PD modeling is also supportive as proof of mechanism in pharmacological animal models (Table 1-II). The decisions of lead optimization and candidate selection are supported based on in vitro-in vivo (IVIV) correlation [23e25]. PK/PD/Efficacy characterization and evaluation of synergistic efficacy of combination therapy may lead to proof of concept in animal models and appropriate dose setting in pharmacological studies [26e29]. Toxicokinetic/Toxicodynamic (TK/TD) analysis can estimate the mechanism of safety issues. Additionally, PK/PD model analysis could verify the appropriateness of biomarkers for the target engagement and/or transduction [30]. Although there is a lot of scientific literature about PK/PD analysis, only the good practice examples seem to be reported. Additionally it was challenging to understand from this literature and from new drug application (NDA) review materials from 2012 to 2017 whether the pharmaceutical industry practically used
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preclinical PK/PD analysis to improve drug discovery and development through deciding the dosage in the clinical trials. Therefore, the Non-Clinical Evaluation Expert Committee in the Japan Pharmaceutical Manufacturers Association (JPMA) conducted a questionnaire survey and compiled the results to comprehend how preclinical PK/PD analysis is currently used at research-based pharmaceutical companies in Japan. 2. Materials and methods The present questionnaire survey was sent to 61 company members of JPMA using the commercial online survey software Qooker (SoftAgency Co., Ltd., Japan). The survey questions included single/multiple choice, Yes/No and free text. The survey consisted of 37 questions aimed to gather information in 6 different areas: “Background”, “Experience”, “Policy and strategy”, “Organization and collaboration”, “Usefulness and purpose” and “Future perspective”. The collection of responses occurred in a period of about 1-month (July to August 2017). All responses to the questionnaire were kept anonymous. Data analysis was conducted using Microsoft Excel (Microsoft Corporation, USA). In addition to simple answer counting, the stratified analysis was also conducted and gave potential reasons as to why certain trends were observed. 3. Results The responses were obtained from 53 companies (response rate: 87%). The majority (66%) of respondents were from companies with 5000 employees and 77% of respondents were Japanese companies. In most companies (97%), the members in the drug metabolism and pharmacokinetics (DMPK) department conducted preclinical PK/PD analyses. Then clinical pharmacology (22%), preclinical pharmacology (19%) and pharmacometrics/Model & Simulation (16%) departments followed (supplemental table S1). All survey questionnaires and responses are presented in the supplemental file. 4. Discussion PK/PD analysis has recently played a greater and more central role in drug discovery and development and its importance is well recognized as an efficient tool for the translational research and proof of mechanism/concept in animals (Table 1). As for the
Table 1 Good practice of preclinical PK/PD analysis based on literature. Item Description I. Translation to clinical study setting from preclinical analysis Target setting (effective dose, regimen, steady-state level etc.) of NME by utilizing clinical information of Integration of comparator/ comparator/competitor with some assumptions (no inter-species differences, correction of in vitro competitor information to potency, etc.). The constructed PK/PD model and target setting for NME can be applicable to selection translation of preclinical and optimization of subsequent candidates. findings of new molecular entity (NME) Mechanism-based quantitative PK/PD modeling can help to predict clinical outcome and select safe and PK/PD modeling-based effective doses and dosing regimens in early clinical development. prediction of clinical outcome/response from preclinical findings II. Support of preclinical proof of concept. IVIV correlation Proof of mechanism of action in preclinical species by confirming the correlation between in vitro (binding or efficiency) and in vivo (target engagement or phenotypic effect). M&S approach is effective to solve the hysteresis and conduct mechanism-based analysis (distinguish the binding and signal transduction). PK/PD/Efficacy or TK/TD Characterize time-dependent PK/PD or TK/TD relationship with quantitative manner. The modeling characterization proves the hypothesis and identifies the unexpected mechanism. The hypothetical scenario can be simulated by the constructed model and it can support candidate optimization. Combination therapy Verify the concept of combination therapy in animals. M&S approach can investigate the additivity with quantitative manner. Various scenarios of dose regimen can be simulated using the developed model. Biomarker for PD Verify the hypothesis that the biomarkers may be useful in pharmacological response. The appropriate biomarker can lead to elucidate the mechanism of action.
Reference [9e15]
[13,16e22]
[23e25]
[26,27]
[28,29] [30]
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translational research, PK/PD models constructed based on the integration of clinical information of comparator/competitor [9e15] and mechanism-based quantitative models [13,16e22] are useful for the prediction of clinical outcomes and the setting of safe and effective doses and dosing regimens in early clinical developments of new molecular entities (NME). And as for the support of preclinical proof of concept, PK/PD M&S approachs are useful for verifying various hypotheses, such as in vitro (binding or efficacy) and in vivo (target engagement or phenotypic effect) (IVIV) correlation [23e25], time-dependent PK/PD or TK/TD relationships [26,27], concept of combination therapy [28,29], and appropriateness of PD biomarkers [30]. However, it is difficult to identify the real practice/application of preclinical PK/PD analysis in pharmaceutical companies from the NDA review documents and scientific literature. The questionnaire survey was conducted and the results were compiled to comprehend how preclinical PK/PD analysis is currently used. Concerning the experience of preclinical PK/PD analysis, 60% of the respondents have experience of conducting preclinical PK/PD analysis, the experienced ratio was higher in the companies with >5000 employees than those with 5000 (Fig. 1A). The numbers of respondents who have experience of conducting preclinical PK/PD analyses and to reflect the PK/PD analysis results to the clinical studies (hereafter called as “PK/PD Experienced Company” and “Translational Company”, respectively) were almost the same between companies with >5000 employees and those with 5000 employees (15 vs 17 or 11 vs 12 companies, Fig. 1A or 1B, respectively). A respondent who has NO experience of reflecting PK/PD analysis results to the clinical studies is referred to as a “No Translational Company”. A respondent who has never conducted PK/PD analysis is referred to as a “PK/PD Inexperienced Company”. Almost all Translational Companies reflected preclinical PK/PD analysis results to Phase 1- study protocols and about half of them also reflected preclinical PK/PD analysis results to POC study protocols (Fig. 1C). The more frequently analyzed therapeutic areas of preclinical PK/PD analysis were neurology, inflammation and metabolic disorders and those were different from the therapeutic areas (infectious disease and oncology) in which PK/PD analysis was considered as effective in the present survey (Fig. 2A and B). However, in the previous survey from 22 pharmaceutical companies conducted by IQ consortium, the therapeutic area that preclinical PK/PD modeling had given the most impact to was oncology [31]. The similar trend showing high expectation of translation of preclinical PK/PD analysis in oncology was observed in the literature reporting good practices of preclinical PK/PD analysis (Table 1). It is not difficult to imagine the importance of preclinical PK/PD analysis, because the patients are enrolled into Phase 1 studies in oncology and so preclinical PK/PD analysis is essential to set the dosing range. The present survey respondents considered that preclinical PK/PD analysis was effective in the oncology area, but the actual implementation ratio was not so high. Although the reason for the difference between the two surveys is unclear, the difference in the constitution of respondents might have some impact on the difference, for example, the majority of the present survey respondents were Japanese companies (77%). In the present survey, the focused therapeutic areas of respondent company is unknown. The analyzed therapeutic areas could highly depend on the focused therapeutic areas in each of the pharmaceutical companies. Therefore, it could be also one of the reason for the low implementation ratio preclinical PK/PD analysis for oncology and infectious disease comparing to effectiveness ratio. In metabolic diseases and infectious diseases, the results by preclinical PK/PD analysis was well reflected to the clinical study
A)
PK/PD nced Inexperienced ny y Company (40%))
≤ 5000 > 5000 PK/PD Experien Experienced Company (60%)
B)
No Translational ational y (28% %) Company (28%) ≤ 5000 > 5000 Translational Compa Company (72%)
C) 91%
Phase 1 POC
52%
Others*
9% 0
10
20
Number of respondent Fig. 1. Experience of preclinical PK/PD analysis and its reflection to the protocol of clinical studies. A) experience of preclinical PK/PD analysis in all respondents, B) reflection of PK/PD analysis to the clinical study protocol in PK/PD Experienced Company, C) clinical study stages designed based on PK/PD analysis in Translational Company. PK/PD Inexperienced Company: a company having no experience of conducting preclinical PK/PD analysis, PK/PD Experienced Company: a company having experience of conducting preclinical PK/PD analysis and consisting of Translational and No Translational Companies. No Translational Company: a company having experience of conducting preclinical PK/PD analysis but no experience to reflect it in clinical studies, Translational Company: a company having experience of reflecting preclinical PK/PD analysis in clinical studies, POC: Proof of concept. Inner pie chart in A) and B) indicates the company size (the number of employees). *:concomitant medication in clinical studies, etc.
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A) TA: analyzed by preclinical PK/PD analysis Infectious disease
C) TA: analyzed using same PD markers or correlated with preclinical data
41%
Oncology
Oncology
41%
Neurology
63%
Inflammation
63%
Metabolic disorders
63% 34%
Others 0
5 10 15 Number of respondent
57%
Infectious disease
53%
Cardiovascular
43%
Cardiovascular
32%
Neurology
43%
Inflammation
32%
Metabolic disorders
64%
Others
20
21% 0
B) TA: effectively analyzed by preclinical PK/PD analysis Infectious disease
71% 71%
Oncology Cardiovascular
45% 65% 52%
Metabolic disorders 35% 0
5 10 15 Number of respondent
Infectious disease
61% 35%
Cardiovascular
30% 48% 39%
Inflammation Metabolic disorders
20
20
D) TA: reflecting the result of preclinical PK/PD analysis to clinical data
Neurology 61%
Others
5 10 15 Number of respondent
Oncology
Neurology Inflammation
151
70% 22%
Others 0
5 10 15 Number of respondent
20
Fig. 2. Therapeutic area (TA) and application degree of preclinical PK/PD analysis. A) TA conducted preclinical PK/PD analysis, B) TA effectively conducted preclinical PK/PD analysis, C) TA conducted clinical PK/PD analysis using the same PD markers or correlated with preclinical data, D) TA reflected the result of preclinical PK/PD analysis to clinical data.
planning and it might be caused by the availability of common PD makers both in preclinical and clinical studies (Fig. 2C and D). Ninety-five percent of the Translational Companies responded that preclinical PK/PD analysis was influential or partially influential on the internal decision making of drug discovery and development (Fig. 3). On the other hand, the same responses were indicated by only 55% of the No Translational Companies. This significant impact on decision making in Translational Companies was consistent with the reflection of preclinical PK/PD analysis on the clinical study planning. In other words, the successful experience of translation might evolve the recognition of the importance of preclinical PK/PD analysis. The respondents' satisfactory degree of collaboration with pharmacologists and clinical pharmacologists was much higher in Translational Companies than those with No Translational Companies (Fig. 4). As described above, most respondents were preclinical DMPK members, and so the collaboration with their pharmacologists was considered to be most important point element for feasibility and appropriateness of PD evaluation. The collaboration with the clinical pharmacologists could be effective to translation and clinical dose prediction. It was suggested that the usefulness of preclinical PK/PD analysis to clinical study planning heavily depended on the collaboration with pharmacology and clinical pharmacology departments. Namely, the usefulness and impact of preclinical PK/PD analyses might be improved by enhancing collaboration with related departments. Even in Translational Companies, there is room for improvement of the satisfactory degree of collaboration with pharmacology and clinical pharmacology, suggesting that the closer collaboration could lead more efficient application of preclinical PK/PD analysis. Additionally, collaboration with toxicologist could be also important in case of TK/TD analysis, even though current questionnaire did not ask about collaboration with toxicologists. For the future perspective, the increase of resources, especially personnel, was highly demanded (Fig. 5). “Education/training” and “Collaboration with other departments” were the most common demands for the major necessities for conducting efficient preclinical PK/PD analyses. The collaboration with other departments is required mostly by Translational Companies followed by No
Translational Companies and PK/PD Inexperienced Companies. It was suggested that the importance of collaboration was more strongly recognized through their experiences of preclinical PK/PD
A) Translational Company (23 companies)
Reference level or not influence (4%)
Influential (43%) Partially influence (52%)
B) No Translational Company (9 companies) Lack of experience or unknown (33%)
Reference level or not influence (11%)
Influential (11%)
Partially influential (44%)
Fig. 3. The impact of the results of preclinical PK/PD analysis on internal decision making. A) Translational Company (23 companies), B) No Translational Company (9 companies).
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(78%), “For the pharmacology studies (70%). The comprehensive analysis of these high ratio purposes could lead the best practice as described in Table 1. These differences in the purpose and usefulness between Translational and No Translational Companies might be the key points for the efficient use of the PK/PD analysis goals. The responses to other questionnaires were listed in Supplemental Table S1. We listed the discussion and interpretation for highly important questions as below.
Fig. 4. Satisfactory degrees of collaboration with other departments for PK/PD analysis. A) With pharmacology departments, B) With clinical pharmacology departments. The percentages in the red boxes represent the ratios of answers “Very satisfied”, “Sufficient” and “So-so” to the total responses.
analysis. The Translational Companies considered that increasing resources for the preclinical PK/PD analysis could lead to efficient drug development (Fig. 6). In the PK/PD Inexperienced Companies and No Translational Companies, the impact on and the applicability of preclinical PK/PD analysis to drug development might be considered as relatively limited. The expected purpose and usefulness of preclinical PK/PD analysis was also investigated (Fig. 7). The leading answer was “relationship of PK and efficacy (78%)” in No Translational Companies, but the ratio of other answers was less than 50%. On the other hand, Translational Companies showed higher ratios in the following answers: “Relationship of PK and efficacy (91%)”, “IVIV relationship of efficacy (87%)”, “For best clinical dosage regimens
Question I-5 and II-3-1: There were some differences on the affiliation between responders and actual PK/PD analysts. It might lead to some bias on the answers for the questionnaire. Question II-4, II-5 and III-9: The responses that the preclinical PK/PD analysis could be applied to more than 70% of their developmental compounds reached only 12 companies out of 32. A comparable number of companies conducted preclinical PK/PD analysis at lead optimization stage and after candidate selection, even though earlier application could be more efficient. The most probable reasons of less and late PK/PD analysis application were suggested absence of appropriate PD markers and the lack of M&S experts. It was suggested that the discovery of PD markers at the early stage could be the key solution. Question II-6: Compared to PK/PD analysis, less companies have experience of TK/TD analysis. The possible reasons might be difficulty of analysis due to non-numerical evaluation of toxicity and unclear detailed mechanism by lack of in vitro evaluation system. The more quantitative safety assessment might enable TK/TD analysis in the future. Question III-1: It was considered that many companies tended to adopt a simple model at first to evaluate the PK/PD relationship. Question III-2: Each type of model was used evenly. It was suggested that an appropriate model was selected based on the pharmacological mechanism or the character of the drugs. Question III-4: Preclinical PK/PD analysis was applied to both small molecule drugs and biological drugs. The response might depend on the focused therapeutic area in the respondent companies, but it was suggested that the preclinical PK/PD analysis is useful to development irrespective of modalities of drugs. Question III-10: Many companies tried to update the PK/PD model after the preclinical stage when they could find a proper PD biomarker or the model was applied to backup candidates. It was considered that they tended to increase the prediction accuracy by updating the model. It might also depend on the timing of initiation of analysis (II-5). Question V-3: Many companies used (or plan to use) the preclinical PK/PD analysis not only for internal decisions, but also
Fig. 5. Expected vision of resource and activities for promoting preclinical PK/PD analysis. A) Preferable resource number for preclinical PK/PD analysis in the future, B) Expected necessary activities to enhance efficient preclinical PK/PD analysis.
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A) PK/PD Inexperienced Company
Other (30%) For supporting to MOA (25%)
B) No Translational Company Other (13%)
For efficient drug development (45%)
For supporting to MOA (38%)
For efficient drug development (50%)
153
C) Translational Company Only prediction of human PK (9%)
Other (4%)
For supporting to MOA (9%)
For efficient drug development (78%)
Fig. 6. Reasons for the response to the question about resource necessity to advance PK/PD analysis in Fig. 5. A) PK/PD Inexperienced Company, B) No Translational Company, C) Translational Company.
regulatory application. Preclinical PK/PD analysis may increase the importance during drug discovery and development. Question VI-4: Only 10 companies out of 32 have used quantitative systems pharmacology (QSP). In the IQ survey, over 90% of companies have had experience [31]. QSP is likely to be expanded in the future as result of the IQ consortium survey about preclinical QSP [32].
A) No Translational Company For pharmacology studies Compound optimization Relationship of PK and efficacy
The present analysis of survey results revealed that the importance of preclinical PK/PD analysis was well recognized among pharmaceutical companies. However, there might be some obstacles against making good use of preclinical PK/PD analysis for more efficient drug discovery and development. Especially, the resource increase in education/training and the collaboration between related departments were suggested to be highly important. Based on the results of the present survey, the authors propose the workflow for the efficient use of preclinical PK/PD analysis as below.
22% 33% 78%
Mode of Action
22%
IVIV relationship of efficacy For optimal Clinical study designs For best Clinical dosage regimens
44% 0%
11% 0
5
10
Number of respondent
B) Translational Company For pharmacology studies Compound optimization Relationship of PK and efficacy
70% 61% 91%
Mode of Action
39%
IVIV relationship of efficacy For optimal Clinical study designs For best Clinical dosage regimens
87% 57% 78% 0
10 Number of respondent
Question VI-5-1 and VI-5-2: Only one-fifth (or about 20%) of the respondent companies thought that the guideline/guidance about PK/PD analysis was necessary. The reasons why many companies did not need it were 1) not preferable to follow, 2) difficult to develop guidelines and 3) no opportunity to follow because the PK/PD analysis result is only used for internal decision making. The requests of preclinical guidelines/guidance might increase if PK/PD analyses were more available and improved to be more effective.
1. Pharmacokinetic experts' involvement in setting the appropriate experimental conditions of pharmacological studies for PK/PD analysis. It is important for pharmacokinetic experts to encourage collaboration especially with pharmacologists in the early stage of drug discovery for identifying the PD markers. 2. Evaluation of the in vitro/in vivo relationship between drug efficacy and drug concentration in plasma or target site quantitatively and time dependently. 3. Translation of the results of preclinical PK/PD analyses to clinical study planning through the discussion with clinical pharmacologists for the setting of the dosage regimens which are expected to show good efficacy and avoid unexpected side effects. 4. After the confirmation and validation of PK/PD model in the clinical study and biological information and/or knowledge accumulation, reverse translation of the model (potentially QSP model) to preclinical research could be efficient for subsequent drug research and development. The proposed workflow would contribute to efficient drug discovery and development and then be sure to lead to an increased success rate of the clinical studies. The further effort for the preclinical PK/PD analysis would be mandatory to get the required resources and skills to expand the use of preclinical PK/PD analysis.
20
Fig. 7. Expected purpose and usefulness for PK/PD analysis. A) No Translational Company, B) Translational Company.
Conflicts of interest We have the following financial relationships to disclose for our manuscript contents.
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Employees: Akihiko Goto (Takeda Pharmaceutical Company Limited), Sadahiro Abe (Pfizer Japan, Inc.), Shoko Koshiba (Kyowa Hakko Kirin Co., Ltd.), Koji Yamaguchi (Chugai Pharmaceutical Co., Ltd., (retired)), Nobuo Sato (Meiji Seika Pharma Co., Ltd.), Yoshikazu Kurahashi (Japan Tobacco Inc.) Declaration of interest Employees of affiliation companies. Author contributions All authors prepared the questionnaire survey, analyzed the results and prepared and reviewed this manuscript. The authors equally contributed to the present work. Acknowledgement The authors gratefully thank the members of the Non-Clinical Evaluation Expert Committee, Drug Evaluation Committee, JPMA for their response to the survey. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.dmpk.2019.01.004. References [1] Paul SM, Mytelka DS, Dunwiddie CT, Persinger CC, Munos BH, Lindborg SR, et al. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat Rev Drug Discov 2010;9(3):203e14. [2] Schuhmacher A, Gassmann O, Hinder M. Changing R&D models in researchbased pharmaceutical companies. J Transl Med 2016;14(1):105. [3] Lave T, Caruso A, Parrott N, Walz A. Translational PK/PD modeling to increase probability of success in drug discovery and early development. Drug Discov Today Technol 2016;21e22:27e34. [4] Ploeger BA, van der Graaf PH, Danhof M. Incorporating receptor theory in mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling. Drug Metab Pharmacokinet 2009;24(1):3e15. [5] Kimko H, Pinheiro J. Model-based clinical drug development in the past, present and future: a commentary. Br J Clin Pharmacol 2015;79(1):108e16. [6] EMEA/CHMP. Guideline on strategies to identify and mitigate risks for first-inhuman and early clinical trials with investigational medicinal products. 2017. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_ guideline/2017/07/WC500232186.pdf. [7] Sato M, Ochiai Y, Kijima S, Nagai N, Ando Y, Shikano M, et al. Quantitative modeling and simulation in PMDA: a Japanese regulatory perspective. CPT Pharmacometrics Syst Pharmacol 2017;6(7):413e5. [8] Manolis E, Brogren J, Cole S, Hay JL, Nordmark A, Karlsson KE, et al. Commentary on the MID3 good practices paper. CPT Pharmacometrics Syst Pharmacol 2017;6(7):416e7. [9] Kreilgaard M, Smith DG, Brennum LT, Sanchez C. Prediction of clinical response based on pharmacokinetic/pharmacodynamic models of 5hydroxytryptamine reuptake inhibitors in mice. Br J Pharmacol 2008;155(2):276e84. [10] Melhem M. Translation of central nervous system occupancy from animal models: application of pharmacokinetic/pharmacodynamic modeling. J Pharmacol Exp Therapeut 2013;347(1):2e6. [11] Maurer TS, Ghosh A, Haddish-Berhane N, Sawant-Basak A, Boustany-Kari CM, She L, et al. Pharmacodynamic model of sodium-glucose transporter 2 (SGLT2) inhibition: implications for quantitative translational pharmacology. AAPS J 2011;13(4):576e84. [12] Liu D, Ma X, Liu Y, Zhou H, Shi C, Wu F, et al. Quantitative prediction of human pharmacokinetics and pharmacodynamics of imigliptin, a novel DPP-4 inhibitor, using allometric scaling, IVIVE and PK/PD modeling methods. Eur J Pharm Sci 2016;89:73e82.
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