Formulation Risk Needs One Accountable Owner: AAPS PharmSci 360 2026

What happens to a protein program when the platform formulation stops fitting the molecule? For Stephanie Johnson, PhD, principal formulation scientist, Pfizer, the answer is less about rescue and more about planning, and that planning starts before the data arrive.

Johnson treats nominating a formulation as the start of continued learning rather than the end of it. “After we nominate a formulation, we’re always learning new things,” she says. Once a candidate is on platform, her team watches for evidence that the molecule is a poor fit:

• a degradation pathway nobody predicted
• a stability signal absent from earlier studies
• aggregation or viscosity that climbs as concentration rises

Any of these can push a program off platform. Johnson describes these departures as routine refinement, not setbacks, because optimization continues throughout development.

Keeping an off-platform move from stalling later-phase work depends on clear accountability. “For this strategy, each risk has exactly one accountable owner,” Johnson says. The formulator owns stability and degradation, the analytical scientist owns data interpretation, and manufacturing owns execution of the batch record. Each risk sits in a register alongside reassessment triggers defined in advance, so the team already knows which findings reopen a decision.

The same rigor applies to the evidence sponsors bring to regulators. Johnson looks for data from comparable molecules developed in the same formulation and process space, tied directly to measurements on the new molecule. “Persuasive prior knowledge is going to be traceable, it’s going to be relevant, and connected to a decision,” she says. Platform knowledge has long been part of the toolkit for compressing development timelines. Johnson stresses being candid about its limits: what the platform reveals about a molecule, and what it leaves unanswered.