Abstract
Antibiotic efficacy determination in clinical trials often relies on non-inferiority designs because they afford smaller study sample sizes. These efficacy studies tend to exclude patients within specific populations or include too few patients to discern potential differences in their clinical outcomes. As a result, dosing guidance in patients with abnormal liver and kidney function, age across the lifespan, and other specific populations relies on drug exposure-matching. The underlying assumption for exposure-matching is that the disease course and the response to the antibiotic are similar in patients with and without the specific condition. While this may not be the case, clinical efficacy studies are underpowered to ensure this is true. The current paper provides an integrative review of the current approach to dose selection in specific populations. We review existing clinical trial endpoints that could be measured on a more continuous rather than a discrete scale to better inform exposure–response relationships. The inclusion of newer systemic biomarkers of efficacy can help overcome the current limitations. We use a modeling and simulation exercise to illustrate how an efficacy biomarker can inform dose selection better. Studies that inform response-matching rather than exposure-matching only are needed to improve dose selection in specific populations.
Highlights
Antimicrobial drug development faces numerous challenges that extend beyond fundamental limitations in discovery platforms [1]
When the disease course and the response to the antibiotic are expected to be similar in adult and pediatric populations, pharmacokinetic (PK) and safety data from adults can be used as a benchmark for dosing in children
Modeling the exposure– response relationships for relevant clinical trial endpoints and biomarkers of efficacy is necessary to improve upon the current paradigm
Summary
Antimicrobial drug development faces numerous challenges that extend beyond fundamental limitations in discovery platforms [1]. A recently published phase 3 study randomized 145 patients to the intervention arm (cefiderocol) and 147 patients to the comparator (meropenem) [2] At face value, these numbers are an order of magnitude lower than those of agents approved for other indications, such as cardiovascular disease [3]. Alternate models for regulatory approval include creating a case for lower quantities of clinical efficacy data to support this unmet medical need [4,5] These range from the acceptance of preclinical data to combinations of a single phase 3 study that is coupled or uncoupled to multiple smaller, pathogen-focused clinical studies [6]. We have multiple case examples where achieving similar systemic exposure values in specific populations may not necessarily lead to comparable clinical outcomes [10]. The use of the term biomarker in this review is a characteristic that is objectively measured as an indicator of pharmacologic response to a therapeutic intervention
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