Systems pharmacology, pharmacogenetics, and clinical trial design in network medicine

The learn‐and‐confirm approach to drug development. First developed by Sheiner,79 this approach can be adapted to incorporate modern systems principles and network medicine to revise, make rational, and facilitate optimization strategies for drug development.

Theoretical dose–toxicity curves (DTCs) for the continuous reassessment method with one patient per cohort. The solid line shows the prior dose–toxicity curve (DTC) from which the dose for the first patient is selected. With a desired doselimiting toxicity (DLT) rate of 0.25, the dose level for the first patient is level 4. The dashed line shows the estimated DTC after observing the first patient if the first patient experienced a DLT. If the first patient experienced a DLT at level 4, then patient 2 would receive dose level 3. The dotted line shows the estimated DTC if the first patient did not experience at DLT at level 4; patient 2 would receive dose level 5. (Reprinted with permission from Ref 57. Copyright 2010 American Association of Cancer Research)

Adaptive dose‐finding study. In an adaptive dose‐finding study, the dose assignment(s) to the next subject, or next cohort of patients, is based on responses of previous subjects, and the dose assignment is chosen to maximize the information about the dose–response curve, according to some predefined objective metric (e.g., variability in parameter estimates). In a traditional dose‐finding trial, selecting a few doses may not adequately represent the dose–response relationship, leading many patients to be allocated to ‘noninformative’ doses (wasted doses), as shown in the figure. In adaptive dose‐finding, the strategy is to include initially only a few patients on many doses to explore the dose–response, then to allocate the dose range of interest to a greater number of patients. This strategy reduces the allocation of patients to noninformative doses. Compared with fixed randomization, this approach has the ethical advantage that fewer subjects are assigned doses that are too high or too low; it can also avoid additional, separate trials that might be necessary when fixed dose‐finding trials do not adequately define the dose range. Adaptive dose‐finding trials also require an infrastructure that allows the rapid communication of responses from trial sites to a central unblinded analysis center and of adaptive dose assignments to the trial sites. Randomization software capable of rapidly computing dynamic allocation of doses to subjects is additionally mandated by adaptive trials because prespecified randomization lists will not work. In addition, a flexible drug‐supply process is required because demand for doses is not fixed in advance, but rather evolves as information on responses at various doses is gathered as the trial progresses. (Reprinted with permission from Ref 9. Copyright 2009 Nature Publishing Group)

A novel model for clinical development. During the exploratory phase of development, this model uses all available knowledge and tools, including biomarkers, modeling, and simulation, as well as advanced statistical methodology. Trials are designed to determine proof‐of‐concept (POC) and to establish dose selection to a level of rigor that will enhance the likelihood of success in the confirmatory phase. During the confirmatory phase, modern designs, tools, and knowledge are applied to larger‐scale studies with the goal of identifying the target patient population in which the drug is efficacious, establishing the benefit‐to‐risk ratio and confirming the optimal dose and dosing regimen. During this phase, innovative clinical trial designs, such as adaptive or seamless studies, compress timelines, improve dose and regimen selection, and reduce the number of patients assigned to nonviable dosing regimens. (Reprinted with permission from Ref 9. Copyright 2009 Nature Publishing Group)

Adaptations to clinical trials. A schematic diagram illustrating the basic structure of a clinical trial is shown in Panel a. Adaptations to clinical trials generally occur at the three levels depicted by the blue arrows shown in Panel b. The sources of information that drive a decision to adapt the trial vary and include data from an external source (Panel c), a prospectively planned analysis of interim data from the trial, and unplanned findings arising from an interim analysis (Panel d). The first two situations are referred to as a reactive revision (Panel c) and an adaptive design (Panel d), respectively.

Pharmacogenetic expression quantitative trait loci (eQTL) study designs. Panel a: Sequential design—comparison of microarray expression profiles of responders (R) with nonresponders (NR) for identification of pharmacogenetic candidates (Step 1), followed by eQTL mapping of candidate gene expression levels in a larger sample (Step 2). Significant eQTLs are subsequently carried to clinical cohorts for classical pharmacogenetic testing (Step 3). Panel b: Perturbation design—time‐series experiment measuring global gene expression in response to drug administration (arrow), testing for SNP‐specific differences in response phenotype (Step 1), which can then be carried forward to clinical testing in Step 2. These designs are not mutually exclusive. (Reprinted with permission from Ref 29. Copyright 2009 Bentham Science Publishers)

The ratio of noncoding to protein‐coding DNA across species; blue circles indicate C. elegans and H. sapiens. (Reprinted with permission from Ref 15. Copyright 2004 Nature Publishing Group)

Schematic diagram illustrating the stages and time course of drug development. Once preclinical testing is complete, the first‐in‐human (FIH) and proof‐of‐concept (POC) studies are performed. These are critical elements of the exploratory phase of drug development, which is followed by the confirmatory phase, characterized by large Phase III, registration‐pathway trials. As emphasized at the bottom of the figure, adaptive design has its greatest utility in guiding the exploratory phase of development. (Reprinted with permission from Ref 2. Copyright 2009 Elsevier)