Portfolio Prioritization for Large and Small Pharma Using Early-Stage Biosimulation

Ideally, drug development resources are directed toward concepts with promising biology and advantageous pharmacology. In practice, too many programs are advanced based on promising biology, only to fail later due to unworkable dosing, weak translatability, or unidentified developability barriers. These problems are often only uncovered after substantial investment by the discovery teams.

In this webinar, Marc Presler and Siak-Leng Choi will overview how integrating mechanistic modeling, literature data, and desired Target Product Profiles were used to improve portfolio decisions before performing substantial experimentation.

Real world impacts include:

1. Directing resources away concepts with poor differentiation or developability.
2. Providing predictions of optimal target drug properties to protein engineers
3. Improving confidence in decision-making for diverse stakeholders

Case studies will review conducting this analysis “at scale” for a large number of concepts at top pharma companies, as well as for small-scale concept optimization at biotechs.

The early-stage biosimulation approach detailed here offers a proven, efficient, and economical strategy to enrich portfolios with viable assets.