Role of Disease Progression Models in Drug Development.

The use of Disease progression models (DPMs) in Drug Development has been widely adopted across therapeutic areas as a method for integrating previously obtained disease knowledge to elucidate the impact of novel therapeutics or vaccines on disease course, thus quantifying the potential clinical benefit at different stages of drug development programs. This paper provides a brief overview of DPMs and the evolution in data types, analytic methods, and applications that have occurred in their use by Quantitive Clinical Pharmacologists. It also provides examples of how these models have informed decisions and clinical trial design across several therapeutic areas and at various stages of development. It briefly describes potential new applications of DPMs utilizing emerging data sources, and utilizing new analytic techniques, and discuss new challenges faced such as requiring description of multiple endpoints, rapid model development, application of machine learning-based analytics, and use of high dimensional and real-world data. Considerations for the continued evolution future of DPMs to serve as community-maintained expert systems are also provided.

Bioequivalence assessment of a pregabalin capsule and oral solution in fasted healthy volunteers: a randomized, crossover study.

OBJECTIVE: To determine the oral bioavailability of a pregabalin capsule relative to a pregabalin solution. METHODS: This was an open-label, randomized, crossover study in 12 healthy volunteers. Pharmacokinetics were compared for a 100-mg capsule and a 100-mg capsule dissolved in water, administered fasted. RESULTS: Mean Cmax and AUC0-∞ for the capsule were within 2% of those for the solution (3.8 vs. 3.7 µg/ml and 26.7 vs. 27.0 µg×h/ml, respectively). The 90% confidence intervals for the ratios of Cmax and AUC0-∞ fell fully within 80 - 125%. CONCLUSIONS: A 100-mg pregabalin capsule is bioequivalent to a pregabalin solution (100-mg capsule dissolved in water).

Population pharmacokinetics of pregabalin in healthy subjects and patients with chronic pain or partial seizures.

PURPOSE: Pregabalin, a high-affinity ligand for α2δ subunits of voltage-gated calcium channels, is a novel pharmacotherapy for chronic pain, partial seizures, and other disorders. The present study investigated the population pharmacokinetics of pregabalin following single and multiple doses in healthy volunteers and patient populations. METHODS: Using nonlinear mixed-effect modeling, 5,583 plasma pregabalin concentration-time samples from 1,723 subjects were analyzed: 2,868 samples from healthy volunteers or subjects with renal impairment (n = 123), 1,513 from patients with partial seizures (n = 626), and 1,202 from patients with chronic pain (n = 974). A one-compartment model with first-order elimination and absorption processes and absorption lag time was used. KEY FINDINGS: This pharmacostatistical model showed that: (1) pregabalin oral clearance (CL/F) was directly proportional to creatinine clearance (CLcr), but was independent of gender, race, age, female hormonal status, daily dose, and dosing regimen; (2) apparent volume of distribution was dependent on body weight and gender; (3) absorption rate was decreased when given with food; and (4) coadministration with marketed antiepileptic drugs (AEDs) had no significant effect on pregabalin CL/F. SIGNIFICANCE: Pregabalin CL/F is related to CLcr, and this relationship is similar among healthy volunteers and patients with either partial seizures or chronic pain disorders. The only factor having a clinically significant influence on steady-state plasma pregabalin concentrations is renal function.

Clinical pharmacokinetics of pregabalin in healthy volunteers.

Pregabalin has shown clinical efficacy for treatment of neuropathic pain syndromes, partial seizures, and anxiety disorders. Five studies in healthy volunteers are performed to investigate single- and multiple-dose pharmacokinetics of pregabalin. Pregabalin is rapidly absorbed following oral administration, with peak plasma concentrations occurring between 0.7 and 1.3 hours. Pregabalin oral bioavailability is approximately 90% and is independent of dose and frequency of administration. Food reduces the rate of pregabalin absorption, resulting in lower and delayed maximum plasma concentrations, yet the extent of drug absorption is unaffected, suggesting that pregabalin may be administered without regard to meals. Pregabalin elimination half-life is approximately 6 hours and steady state is achieved within 1 to 2 days of repeated administration. Corrected for oral bioavailability, pregabalin plasma clearance is essentially equivalent to renal clearance, indicating that pregabalin undergoes negligible nonrenal elimination. Pregabalin demonstrates desirable, predictable pharmacokinetic properties that suggest ease of use. Because pregabalin is eliminated renally, renal function affects its pharmacokinetics.

How modeling and simulation have enhanced decision making in new drug development.

The idea of model-based drug development championed by Lewis Sheiner, in which pharmacostatistical models of drug efficacy and safety are developed from preclinical and available clinical data, offers a quantitative approach to improving drug development and development decision-making. Examples are presented that support this paradigm. The first example describes a preclinical model of behavioral activity to predict potency and time-course of response in humans and assess the potential for differentiation between compounds. This example illustrates how modeling procedures expounded by Lewis Sheiner provided the means to differentiate potency and the lag time between drug exposure and response and allow for rapid decision making and dose selection. The second example involves planning a Phase 2a dose-ranging and proof of concept trial in Alzheimer's disease (AD). The issue was how to proceed with the study and what criteria to use for a go/no go decision. The combined knowledge of AD disease progression, and preclinical and clinical information about the drug were used to simulate various clinical trial scenarios to identify an efficient and effective Phase 2 study. A design was selected and carried out resulting in a number of important learning experiences as well as extensive financial savings. The motivation for this case in point was the "Learn-Confirm" paradigm described by Lewis Sheiner. The final example describes the use of Pharmacokinetic and Pharmacodynamic (PK/PD) modeling and simulation to confirm efficacy across doses. In the New Drug Application for gabapentin, data from two adequate and well-controlled clinical trials was submitted to the Food and Drug Administration (FDA) in support of the approval of the indication for the treatment of post-herpetic neuralgia. The clinical trial data was not replicated for each of the sought dose levels in the drug application presenting a regulatory dilemma. Exposure response analysis submitted in the New Drug Application was applied to confirm the evidence of efficacy across these dose levels. Modeling and simulation analyses showed that the two studies corroborate each other with respect to the pain relief profiles. The use of PK/PD information confirmed evidence of efficacy across the three studied doses, eliminating the need for additional clinical trials and thus supporting the approval of the product. It can be speculated that the work by Lewis Sheiner reflected in the FDA document titled "Innovation or Stagnation: Challenge and Opportunity on the Critical Path to New Medical Products" made this scientific approach to the drug approval process possible.