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January 26, 2026

In the high-stakes world of drug development, success is never guaranteed. Even with advances in target discovery, biomarkers, biologics, and computational methods, most drug candidates entering clinical development still do not make it to approval. That uncertainty shapes every major decision: funding strategy, clinical planning, partnering discussions, and ultimately how an organization thinks about drug asset valuation.

To explore what separates programs that gain traction from those that stall, we spoke with two leaders who evaluate assets through both a development and investment lens: Fran Brown and Amy Cheung of Certara Drug Development Solutions.

Success is rarely about science alone

Fran addressed the difficult reality behind development risk:

“Once you enter clinical development, the probability of actually getting an approved compound is about ten percent. Ninety percent of drugs that enter the clinic fail for multiple reasons.”

Whether an asset advances depends on far more than scientific novelty.

“At the core is the data on the compound and the program itself, but many other elements come into play: team expertise, infrastructure, development plans, risk mitigation, commercial potential, and intellectual property.”

Innovative biology does not automatically translate into a clinically or commercially viable program. The assets that succeed are those prepared to withstand the clinical, regulatory, and competitive pressures that ultimately determine their value.

Why early decisions are so difficult

The most expensive and irreversible decisions often occur when evidence is least complete. Executives must prioritize programs. Business development teams must shape partnering strategies. Investors need confidence before committing capital. Yet due diligence is expected to be rapid and evidence-driven while relying on imperfect information.

This tension is where Model-Informed Drug Development (MIDD) is becoming influential, particularly as regulatory acceptance grows, and frameworks such as ICH M15 formalize the role of modeling in decision-making.

A more confident way to predict what will happen in patients

Amy described MIDD as a way to transform existing evidence into actionable insight:

“MIDD turns good data into predictive data, showing that what you have seen is not just plausible but quantitatively reproducible through modeling and simulation.”

Rather than relying on intuition, teams can test assumptions early, estimating dose confidence, subgroup response, exposure-response relationships, therapeutic window, and competitive positioning before committing to the next clinical step.

“With modeling we can reconstruct the exposure-response relationship even when raw datasets are not available and then simulate different dosing and population scenarios to quantify risk.”

Virtual patient simulations, digital twins in drug development, and AI-enabled approaches now allow organizations to explore likely human outcomes before years of trials unfold.

What this means for developers and investors

A clear theme emerged: MIDD has evolved from a technical tool into a strategic lever that directly informs how confidently an asset can be evaluated.

When teams can anticipate performance across multiple scenarios, they can:

  • avoid preventable failures
  • support valuation with quantitative evidence
  • shape clinical strategy before enrollment
  • strengthen partnering and licensing discussions

For investors, this offers clarity beyond traditional data packages. For developers, it enables a more credible and defensible asset narrative. Whether in oncology, rare disease, or early translational programs, quantitative confidence is becoming a differentiator in how assets are viewed.

The takeaway

Everyone in drug development is working toward the same goal: advancing therapies to patients who need them. Yet without the right evidence early, organizations are too often forced to make high-consequence decisions based on hope rather than probability.

MIDD does not eliminate risk, but it provides a clearer lens for evaluating it. And that clarity is increasingly central to informed, credible drug asset valuation.

Erika Brooks

Marketing Director, Quantitative Science Services

With over 22 years of experience in hospitals, health systems, associations, life sciences, physician practices, and suppliers, Erika is an experienced marketing strategist and supports the Quantitative Science Services offering with Go-to market planning and execution.

With insights from:

Vice President, Europe/APAC Regional Lead of Quantitative Science, Global Lead of Certara’s Pediatric and Maternal Innovation Engine

Dr. Cheung has more than 20 years of experience in modeling and simulation, as well as clinical pharmacology, with expertise in PBPK/PD mechanistic modelling, special populations (e.g., pediatrics, maternal, and geriatrics), extrapolation, model-based meta-analysis, vaccines, infections, HIV, complex biologics, and different therapeutic areas across early, late-phase and post marketing drug development. She is an honorary professor at the School of Engineering at the University of Warwick, UK. She is leading the EU funding project, ERAMET (grant agreement number 101137141), in work package 5, championing the enhancement and utilization of extrapolation in pediatric populations and for rare diseases.

Vice President, Global Head, Drug Development Science

Dr. Fran Brown is a highly respected professional with proven leadership skills and 28 years of broad experience within pharmaceutical development and due diligence. She has extensive experience with strategic and operational global drug development from early discovery to filing and post-marketing. This experience spans multiple therapeutic areas, small molecules and biologics, global regulatory requirements and registration pathways. She possesses a broad knowledge of product development and portfolio management, with a special focus on development strategy, regulatory interactions and product filings.

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