Predictive Models and Raw Immunogenicity Data Could Reshape Preclinical Development, Says Vibha Jawa

As regulators continue pushing for reduced animal use in drug development, biopharmaceutical companies are increasingly exploring predictive models and alternative analytical approaches to support preclinical decision-making, according to Vibha Jawa, PhD, who spoke with BioPharm International during AAPS National Biotech Conference 2026.

In her presentation entitled What’s Required vs. What’s Possible: Translational Bioanalytics for IND Success, delivered Wednesday, March 13, 2026, at AAPS NBC, Jawa described how advances in translational science and data analysis may help sponsors streamline preclinical programs while generating more clinically relevant insights for investigational new drug (IND)-enabling packages.

“There’s a lot more data which can be now mined back to make predictive models, whether they’re mathematical models or even more human relevant physiological models, so that we don’t have to rely on animals,” Jawa said in the interview.

She explained that while animal studies have historically played a major role in evaluating biologics safety and pharmacology, regulators including FDA and EMA are increasingly recognizing limitations in some traditional preclinical approaches. According to Jawa, animal models may sometimes exaggerate pharmacologic or immune responses compared with humans, creating opportunities to refine development strategies.

Could Raw Immunogenicity Data Replace Traditional Titer Approaches?

Jawa also discussed evolving perspectives on immunogenicity testing for biologics, particularly the limitations of traditional antibody titer methodologies adapted from vaccine development.

“We do not need to dilute our samples to do titers,” Jawa said. “We could look at the patient’s raw readouts.”

According to Jawa, biologics are intentionally engineered to minimize immune responses, making conventional vaccine-style titer approaches potentially less informative in some settings. Instead, she described growing interest in evaluating longitudinal “signal-to-noise” immune response data derived directly from assay platforms such as electrochemiluminescence and ELISA systems.

Jawa noted that traditional tiered immunogenicity workflows—including screening, confirmatory testing, and titer analysis—may unintentionally filter out clinically relevant variability in patient responses. She also questioned reliance on fixed assay cut points, suggesting they may not adequately reflect the nuanced immune profiles observed with biologic therapies.

The broader shift toward predictive modeling, human-relevant systems, and more individualized immune monitoring reflects ongoing efforts across the biopharmaceutical industry to modernize preclinical and translational development practices.

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About the speaker

Vibha Jawa, PhD., FAAPS, Chief Scientific Officer, EpiVax, Inc.

Dr. Vibha Jawa is Chief Scientific Officer at EpiVax, where she leads scientific strategy and innovation in immunogenicity and translational science. Previously, she held leadership roles at Bristol Myers Squibb, Merck, and Amgen, supporting biologics, vaccines, and cell and gene therapy development. With more than 20 years of industry experience, she has contributed to more than 20 IND, BLA, and MAA filings. Jawa has authored more than 75 peer-reviewed publications and serves in multiple leadership roles within AAPS and other scientific organizations. She was named an AAPS Fellow in 2022.