Tyler Dunlap, Pharm.D., DABCP, Brian Corrigan, Ph.D., Marc Gastonguay, Ph.D

Presented at the 2026 Annual Meeting of the American College of Clinical Pharmacology (ACCP 2026), on September 27, 2026. Winner of the 2026 ACCP Early-Stage Professional Abstract award. 

Biopharmaceutical research and development (R&D) productivity, defined as the aggregate return on investment for all drug development activities, is declining despite rapid technological advancement. While a multifactorial challenge, this trend is exacerbated by increasingly complex therapeutic modalities and rudimentary decision-making frameworks. While Model-Informed Drug Development (MIDD) has become an established scientific framework among clinical pharmacologists, its contribution to strategic risk management remains underleveraged. This work builds upon previous efforts to integrate pharmacometric, commercial, and financial valuation models into a quantitative decision framework to improve R&D productivity. Here, we propose a framework for identifying the mechanistic drivers of risk for clinical trial failure for a hypothetical Phase 3 study.

Yuchen Wang¹, Matthew Wiens², Ke Szeto¹, Timothy Waterhouse², Vivek Purohit¹, Leandro L. Santos³, Jessica Wojciechowski¹
¹Clinical and Quantitative Pharmacology, Incyte Corporation, Wilmington, DE, USA; ²Metrum Research Group, Boston, MA, USA; ³Clinical Development, Incyte Corporation, Wilmington, DE, USA

Presented at the 2026 American Conference on Pharmacometrics (ACoP 2026), an International Conference on Pharmacometrics in the US (ICoP – US), on October 14, 2026.

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease characterized by recurrent nodules, abscesses, and draining tunnels (dTs) that contribute substantially to disease burden. The presence of dTs is indicative of irreversible tissue damage, and a surrogate marker of a more challenging to treat HS, making dT count (dTC) a clinically meaningful endpoint. Povorcitinib is an oral, highly selective Janus kinase 1 inhibitor with demonstrated efficacy in reducing dTC in the phase 3 STOP-HS1 and –HS2 studies. Because dTC changes dynamically over time, a continuous-time Markov model (birth-death process) was developed to characterize the longitudinal relationship between povorcitinib exposure and dTC in patients with moderate to severe HS.

Andrew Tredennick¹, Matthew Weins¹, Timothy Knab¹, Cole Zmurchok¹, Ahmed Elmokadem²
¹ Metrum Research Group, Boston, MA, USA; ² GlaxoSmithKline (GSK), Collegeville, PA, USA

Presented at the 2026 American Conference on Pharmacometrics (ACoP 2026), an International Conference on Pharmacometrics in the US (ICoP – US), on October 14th, 2026.

Virtual populations (VPops) are widely used in quantitative systems pharmacology (QSP) to represent variability in clinical populations and support model calibration and simulation of treatment outcomes. Practical guidance on selecting among algorithms to generate VPops, and understanding their relative performance, remains limited. The objective of this work was to compare commonly used and emerging VPop generation approaches based on data-simulation matching and computation time.

Presented at the PGRN 2025 Scientific Meeting, held in collaboration with ClinPGx, September 10–12, 2025 at the University of Montana in Missoula, where together leaders in pharmacogenomics and clinical pharmacology came together to advance the science and practice of precision medicine.

Pharmacogenetics (PGx) provides critical insights into how genetic variability influences drug metabolism, disposition, and response. This presentation highlights how when incorporated into population PK models, PGx information can:

• Identify subgroups with distinct pharmacokinetic profiles
• Improve predictions of individual dose–response relationships
• Support precision dosing strategies that optimize efficacy while minimizing toxicity

Integrating PGx into quantitative modeling is a powerful step toward making personalized medicine a clinical reality.

This study presents a validated whole-body PBPK model characterizing drug-drug interactions (DDIs) involving posaconazole, a broad-spectrum antifungal, in individuals with normal weight and obesity. Findings highlight a prolonged half-life and irreversible CYP3A4 inhibition in patients with BMI ≥35 kg/m², underscoring the increased risk of DDIs even after discontinuation. The model supports optimized dosing and risk assessment for co-administered CYP3A4-sensitive drugs.

This work illustrates how integrated population PK modeling of antibody-conjugated payload and free payload analytes for an ADC can inform development strategies for targeted therapies—particularly in complex oncology settings.

A companion poster to the ASCPT print copy, this visual presentation emphasizes the simulation approach used to evaluate individualized dosing strategies and their economic implications. Results underscore the importance of reducing discontinuation rates to enhance value.

This study uses pharmacometric and pharmacoeconomic modeling to explore the cost effectiveness of individualized dosing for a hypothetical new atopic dermatitis drug compared to dupilumab. Simulation scenarios tested the impact of treatment discontinuation rates, efficacy variability, and pricing on cost utility outcomes.