- Email: [email protected]
pharmacodynamic studies in the CMI
Accepted Manuscript Pharmacokinetic/Pharmacodynamic studies in the CMI William Couet, CMI Editorial PII:
S1198-743X(16)30308-1
DOI:
10.1016/j.cmi.2016.08.005
Reference:
CMI 684
To appear in:
Clinical Microbiology and Infection
Received Date: 9 August 2016 Accepted Date: 10 August 2016
Please cite this article as: Couet W, Pharmacokinetic/Pharmacodynamic studies in the CMI, Clinical Microbiology and Infection (2016), doi: 10.1016/j.cmi.2016.08.005. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT 1
Editorial Note
2
Pharmacokinetic/Pharmacodynamic studies in the CMI
4
William Couet
5
CMI Editorial
RI PT
3
6
Inserm U-1070, Pôle Biologie Santé, Poitiers, France
8
Université de Poitiers, UFR Médecine-Pharmacie, Poitiers, France
9
CHU Poitiers, Service de Toxicologie-Pharmacocinétique, Poitiers, France
M AN U
10
Pôle Biologie Santé, 1 rue Georges Bonnet - BP 633
12
86022 Poitiers Cedex
13
France
TE D
11
14
E-mail: [email protected]
16
Phone : + (33) 5 49 45 43 79
17
Fax : + (33) 5 49 45 43 78
AC C
19
EP
15
18
SC
7
ACCEPTED MANUSCRIPT Antibiotic resistance is a complex and major threat to our societies with obvious major
21
consequences on health care. It also has environmental, social, and economic impacts (1).
22
Every initiative that may help to overcome this challenge should be encouraged. New
23
antibiotics are urgently needed but their development is complex, takes time, and return on
24
investment is often questionable. International collaborative programs co-funded by private
25
firms and the public domain, such as the European program IMI « New drugs for bad bugs »,
26
have already been created to favor the development of new antibiotics.
RI PT
20
SC
27
But other initiatives to tackle antibiotic resistance are needed as well. Old forgotten antibiotics
29
may constitute a valuable alternative to treat infections caused by pathogens resistant to most
30
of the currently used antibiotics. Colistin is a good example of this. These old drugs present
31
the advantage of being already available and well known in in terms of safety. However, they
32
also have the disadvantage of not being protected by patents anymore. Costly clinical trials
33
conducted according to modern standards are necessary to demonstrate their efficacy in
34
patients infected by bacteria with new resistance mechanisms (2). The best possible dosing
35
regimen should be selected on rational pharmacokinetic/pharmacodynamic (PK/PD) basis; in
36
order not only to increase clinical success likelihood, but also to avoid sub-optimal exposure
37
that favors the development of resistances. Therefore, CMI welcomes PK/PD articles
38
providing important missing information in order to properly use new or old antibiotics, alone
39
or in combination, for the treatment of difficult to treat infections due to multiple drug
40
resistant (MDR) bacteria.
AC C
EP
TE D
M AN U
28
41 42
Optimal dosing regimen selection is probably an important way to avoid resistant mutant
43
selection, and new paradigms are necessary to better understand and describe the influence of
44
dosing on resistance. On the PK side, population approaches and Bayesian forecasting
ACCEPTED MANUSCRIPT constitutes modern tools to properly control the dose-concentration relationship, even on an
46
individual basis when necessary. But on the PD side the minimum inhibitory concentration
47
(MIC) or the mutant prevention concentration (MPC) cannot integrate the complex
48
phenomenon responsible for decreased bacteria susceptibility observed over time in patients
49
when antibiotic concentrations are changing with time. A huge number of recent papers
50
describe mechanisms of resistance at a molecular level, providing a considerable amount of
51
information. Unfortunately, this information cannot be used for dosing regimen optimization
52
using current traditional PK/PD approaches. This is especially true when antibiotics are given
53
in combinations as most often the case with difficult to treat infections.
SC
RI PT
45
M AN U
54
Semi-mechanistic PK/PD modeling is intended to integrate various phenomena leading to
56
decreased bacteria susceptibility in relatively simple models that can be used for optimal
57
dosing regimen. Recent advances in model based drug development have had a huge impact
58
on optimal dose determination in many therapeutic areas. Only a limited number of articles
59
have been published describing semi-mechanistic PK/PD modeling of antibiotics, meaning
60
that the approach is not yet very popular. However, it seems to be very promising as the most
61
powerful translational approach to integrate the complexity of antibiotic resistance from
62
bench to bed (3). Therefore, CMI encourages articles based on innovative semi-mechanistic
63
PK/PD modeling approaches with translational potential to clinical practice.
EP
AC C
64
TE D
55
65
Manuscripts will be considered for publication if they report for the first time
66
pharmacokinetic data of a new antimicrobial agent in humans; or present new clinical
67
population pharmacokinetic data and target attainment of a known antibiotic in a new
68
indication, a new dosing regimen strategy or drug-drug combination, a new specific sub-
69
group of patients, or use unbound tissue concentrations at the infection site instead of total
ACCEPTED MANUSCRIPT 70
plasma concentrations, or contribute to the development of new innovative approaches such
71
as
72
pharmacokinetic/pharmacodynamics (PK/PD) modeling, that may better predict antimicrobial
73
activity or emergence of resistance in patients than traditional approaches.
physiologically
based
pharmacokinetic
(PB/PK)
modeling,
or
mechanistic
75
RI PT
74
Editorial Note: Not Peer-reviewed
76
81 82 83
84
SC
M AN U
80
sustainable development. Ups J Med Sci. 2016; 121(3): 159-64. 2. Theuretzbacher U, Paul M. Revival of old antibiotics: structuring the re-development process to optimize usage. Clin Microbiol Infect. 2015; 21(10): 878-80. 3. Nielsen EI, Friberg LE., Pharmacokinetic-pharmacodynamic modeling of antibacterial
TE D
79
1. Jasovský D, Littmann J, Zorzet A, Cars O. Antimicrobial resistance-a threat to the world's
drugs. Pharmacol Rev. 2013; 65(3): 1053-90.
EP
78
References:
AC C
77
S1198-743X(16)30308-1
DOI:
10.1016/j.cmi.2016.08.005
Reference:
CMI 684
To appear in:
Clinical Microbiology and Infection
Received Date: 9 August 2016 Accepted Date: 10 August 2016
Please cite this article as: Couet W, Pharmacokinetic/Pharmacodynamic studies in the CMI, Clinical Microbiology and Infection (2016), doi: 10.1016/j.cmi.2016.08.005. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT 1
Editorial Note
2
Pharmacokinetic/Pharmacodynamic studies in the CMI
4
William Couet
5
CMI Editorial
RI PT
3
6
Inserm U-1070, Pôle Biologie Santé, Poitiers, France
8
Université de Poitiers, UFR Médecine-Pharmacie, Poitiers, France
9
CHU Poitiers, Service de Toxicologie-Pharmacocinétique, Poitiers, France
M AN U
10
Pôle Biologie Santé, 1 rue Georges Bonnet - BP 633
12
86022 Poitiers Cedex
13
France
TE D
11
14
E-mail: [email protected]
16
Phone : + (33) 5 49 45 43 79
17
Fax : + (33) 5 49 45 43 78
AC C
19
EP
15
18
SC
7
ACCEPTED MANUSCRIPT Antibiotic resistance is a complex and major threat to our societies with obvious major
21
consequences on health care. It also has environmental, social, and economic impacts (1).
22
Every initiative that may help to overcome this challenge should be encouraged. New
23
antibiotics are urgently needed but their development is complex, takes time, and return on
24
investment is often questionable. International collaborative programs co-funded by private
25
firms and the public domain, such as the European program IMI « New drugs for bad bugs »,
26
have already been created to favor the development of new antibiotics.
RI PT
20
SC
27
But other initiatives to tackle antibiotic resistance are needed as well. Old forgotten antibiotics
29
may constitute a valuable alternative to treat infections caused by pathogens resistant to most
30
of the currently used antibiotics. Colistin is a good example of this. These old drugs present
31
the advantage of being already available and well known in in terms of safety. However, they
32
also have the disadvantage of not being protected by patents anymore. Costly clinical trials
33
conducted according to modern standards are necessary to demonstrate their efficacy in
34
patients infected by bacteria with new resistance mechanisms (2). The best possible dosing
35
regimen should be selected on rational pharmacokinetic/pharmacodynamic (PK/PD) basis; in
36
order not only to increase clinical success likelihood, but also to avoid sub-optimal exposure
37
that favors the development of resistances. Therefore, CMI welcomes PK/PD articles
38
providing important missing information in order to properly use new or old antibiotics, alone
39
or in combination, for the treatment of difficult to treat infections due to multiple drug
40
resistant (MDR) bacteria.
AC C
EP
TE D
M AN U
28
41 42
Optimal dosing regimen selection is probably an important way to avoid resistant mutant
43
selection, and new paradigms are necessary to better understand and describe the influence of
44
dosing on resistance. On the PK side, population approaches and Bayesian forecasting
ACCEPTED MANUSCRIPT constitutes modern tools to properly control the dose-concentration relationship, even on an
46
individual basis when necessary. But on the PD side the minimum inhibitory concentration
47
(MIC) or the mutant prevention concentration (MPC) cannot integrate the complex
48
phenomenon responsible for decreased bacteria susceptibility observed over time in patients
49
when antibiotic concentrations are changing with time. A huge number of recent papers
50
describe mechanisms of resistance at a molecular level, providing a considerable amount of
51
information. Unfortunately, this information cannot be used for dosing regimen optimization
52
using current traditional PK/PD approaches. This is especially true when antibiotics are given
53
in combinations as most often the case with difficult to treat infections.
SC
RI PT
45
M AN U
54
Semi-mechanistic PK/PD modeling is intended to integrate various phenomena leading to
56
decreased bacteria susceptibility in relatively simple models that can be used for optimal
57
dosing regimen. Recent advances in model based drug development have had a huge impact
58
on optimal dose determination in many therapeutic areas. Only a limited number of articles
59
have been published describing semi-mechanistic PK/PD modeling of antibiotics, meaning
60
that the approach is not yet very popular. However, it seems to be very promising as the most
61
powerful translational approach to integrate the complexity of antibiotic resistance from
62
bench to bed (3). Therefore, CMI encourages articles based on innovative semi-mechanistic
63
PK/PD modeling approaches with translational potential to clinical practice.
EP
AC C
64
TE D
55
65
Manuscripts will be considered for publication if they report for the first time
66
pharmacokinetic data of a new antimicrobial agent in humans; or present new clinical
67
population pharmacokinetic data and target attainment of a known antibiotic in a new
68
indication, a new dosing regimen strategy or drug-drug combination, a new specific sub-
69
group of patients, or use unbound tissue concentrations at the infection site instead of total
ACCEPTED MANUSCRIPT 70
plasma concentrations, or contribute to the development of new innovative approaches such
71
as
72
pharmacokinetic/pharmacodynamics (PK/PD) modeling, that may better predict antimicrobial
73
activity or emergence of resistance in patients than traditional approaches.
physiologically
based
pharmacokinetic
(PB/PK)
modeling,
or
mechanistic
75
RI PT
74
Editorial Note: Not Peer-reviewed
76
81 82 83
84
SC
M AN U
80
sustainable development. Ups J Med Sci. 2016; 121(3): 159-64. 2. Theuretzbacher U, Paul M. Revival of old antibiotics: structuring the re-development process to optimize usage. Clin Microbiol Infect. 2015; 21(10): 878-80. 3. Nielsen EI, Friberg LE., Pharmacokinetic-pharmacodynamic modeling of antibacterial
TE D
79
1. Jasovský D, Littmann J, Zorzet A, Cars O. Antimicrobial resistance-a threat to the world's
drugs. Pharmacol Rev. 2013; 65(3): 1053-90.
EP
78
References:
AC C
77