PharmaForceIQ today introduced Share of Answer, the newest capability in its Optichannel 360 platform, to bridge the gap between AI visibility audits and real-world execution. The module helps biopharma companies evaluate how their therapies are represented in AI-generated answers to clinical and disease-related questions and identify opportunities to improve accuracy and visibility.
In recent PharmaForceIQ analyses, brand and condition websites accounted for just 17% of AI-answer citations on average. The audits also identified hundreds of retired webpages and instances of superseded FDA-approved labeling appearing in AI-generated responses. The findings highlight the challenges pharma faces: ensuring that AI-generated health information from large language models (LLMs) reflects current, reliable clinical evidence.
Share of Answer (SOA) is the proportion of relevant AI responses in which a therapy or brand is present and represented accurately. As healthcare professionals (HCPs) and patients increasingly use AI tools, any inaccurate, outdated, or incomplete answers can affect how they understand diseases and treatment options.
Unlike tools that monitor surface-level mentions, this product audits each answer claim by claim and turns the findings into prioritized fixes. The system diagnoses AI positioning, establishes an MLR-governed source of truth, and publishes approved claims on relevant digital channels where AI engines can read and cite them, with each statement traced back to a clear source. The module has supported analyses of more than 10,000 AI-generated responses across branded and disease-state programs at biopharma companies of different sizes. Across disease education and brands, its evaluation framework examines four dimensions:
- Present: Is the brand, molecule or therapy surfaced in relevant clinical and disease-state queries?
- Accurate: Is the answer faithful to current approved evidence, without unsupported claims, outdated dosing, or withdrawn data?
- Preferred: How is the therapy presented relative to alternatives? Does the response convey meaningful clinical differentiation?
- Cited: Does the response reference authoritative sources, such as peer-reviewed clinical trials and treatment guidelines?
PharmaForceIQ’s Chief Executive and Strategy Officer Hemal Somaiya said: “We’ve seen a massive shift in how HCPs discover scientific information. When a clinician asks AI about a therapy, the answer should reflect accurate evidence that the brand stands behind instead of outdated information or unsupported claims. Share of Answer gives pharma teams a way to understand how their therapies are represented and where additional evidence or content can make a difference.”
Data from recent visibility audits shows significant gaps and substantial variation across AI engines:
- Approved content was rarely cited: Official brand and condition websites accounted for 17% of citations on average across the analyses.
- Outdated sources remained visible: The audits identified citations to hundreds of retired webpages. In one analysis, AI-generated responses quoted superseded FDA-approved labeling in nearly 250 answers.
- Disease abbreviations led to identification errors: In an analysis of a rare disease, AI engines correctly identified the condition when prompted with its full name, but more than half of the answers failed to identify it when an abbreviation was used.
By helping teams publish approved content–accounting for how HCPs search for information and how answer engines find it–this tool empowers pharma teams to move beyond identifying gaps to solving for them. In one controlled test of a subset of questions, answer accuracy rose to 94–100% (and one engine went from 40% to 95%).
This Share of Answer module is part of Optichannel 360, the company’s AI-native commercial execution platform connecting field and digital marketing. Learn more at pharmaforceiq.com.
