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Examples of Our Work in HIV

Using in vitro and literature data to predict effects of new antiretrovirals

Planning a Phase IIa trial, understanding a Phase IIb failure®

Selecting Doses for Proof-of-Concept Monotherapy and for Large-Scale Combination Therapy

Dose Selection for HIV Therapy: Case Study of a Pfizer-Pharsight Collaboration

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Modeling and Simulation to Assess Dosing Regimen and Support Design of a Dose-Response Monotherapy Study in HIV-1 Infected Patients

Modeling and Simulation of DEBIO-025 in HIV
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Optimization of Trial Design through Integration of Drug-Disease, Financial, and Decision Modeling

Three doses of a new HIV therapy were to be tested with a standard background regimen. A new PK interaction study showed an unexpected reduction of the background drug concentrations at the highest dose of the new drug. The client faced an urgent question: should the high-dose arm be dropped?

Skipping the high-dose arm would save time and money. The team had been focusing on avoiding $400,000 of extra blinding and trial costs, and three months of delay in time to market valued at $8 million. However, the analysis showed that skipping the high-dose arm would risk losing $300 million expected value in a development success scenario. Using a simple decision tree to weigh the alternatives, a sensitivity analysis showed that only extreme, implausible combinations of success probabilities for the three planned arms should lead to dropping the high-dose arm.

The project confirmed the decision to keep the arm, provided confidence in the decision and alignment of the project team, could have saved significant trial resources, and demonstrated the importance of an integrated approach to drug disease, financial, and decision modeling.