Pharmaceutical companies invest more than$300 billionannually in research and development, but of the drugs that enter clinical trials, only a small fraction ultimately receive approval from the U.S. Food and Drug Administration (FDA).12%。

Even when a therapy succeeds, commercialization still depends on identifying eligible patients and their treating physicians; as treatments become more targeted and enrollment criteria more complex, this challenge intensifies. Diagnostic data is becoming a strategic asset.

"Pharmaceutical companies can use predictive analytics built on laboratory results and claims to validate hypotheses, estimate market size, and prioritize physician outreach to educate them about patient and diagnostic pathways," said Parag More, Executive Director of Life Sciences Data and Analytics Solutions at Quest Diagnostics. "This leads to smarter, data-driven launch strategies."

Predictive analytics leverages real-world laboratory data to help transform market access strategies, expanding eligible patient populations from diagnosed to undiagnosed and underdiagnosed groups, identifying National Provider Identifiers (NPIs) of physicians treating patients, and accelerating therapy adoption.

The Commercialization Gap

FDA approval is not the end of drug development, but the beginning of another critical phase—commercialization.

Therapies are becoming increasingly specialized, including precision medicine and rare diseases, making patient identification more complex. This is especially true for patients with complex or delayed diagnostic pathways, who often receive fragmented care across multiple healthcare systems. If the right patients and physicians are not identified early in commercialization, a therapy may struggle to gain market traction.

Pharmaceutical companies are increasingly investing in advanced analytics to bridge these gaps. Data-driven commercialization strategies, including predictive analytics and real-world data analysis, are becomingkey to improving commercial performance and optimizing launches。

"Commercial success depends on knowing where eligible patients are in the healthcare system and which physicians are treating them," More said. "Without this near real-time visibility, even breakthrough therapies can face slow adoption."

Laboratory testing generates longitudinal real-world clinical insights, providing visibility into disease prevalence, testing patterns, and progression. Compared to retrospective analyses that identify known eligible patients, predictive modeling can identify "hidden" or undiagnosed patients matching target characteristics, map disease progression and high-risk cohorts, and identify physicians treating eligible populations through de-identified patient data, thus going beyond simple retrospective analysis to proactively identify potential patients. In addition to helping commercial teams understand where patient populations are concentrated and which physicians are most likely to encounter them in practice, predictive analytics can also inform market size estimation and launch planning.

Leveraging diagnostic data as a strategic asset enables more precise education and outreach, and supports sponsored testing programs to narrow diagnostic gaps.

"When we use predictive analytics to identify undiagnosed populations, commercial teams can reach out to their physicians to educate them about the patient journey and the tests that can aid in diagnosis," More said. "As a result, physicians can ensure patients receive accurate and timely diagnoses, reducing their uncertainty and helping them get on the right treatment path faster."

Diagnostic Data as a Strategic Asset

More than12 billionmedical laboratory tests are analyzed in the U.S. each year, creating vast and diverse datasets that provide insights into disease prevalence, testing patterns, and progression, and bridging the gap between approval and adoption. As therapies become more targeted and market competition intensifies, commercialization strategies must become more data-driven.

"Diagnostic laboratory data is one of the most valuable yet underutilized sources of healthcare insights," More said. "It captures the diagnostic journey—from early abnormal results to confirmatory testing—and this visibility creates opportunities to identify patients earlier in the care pathway."

Organizations that treat diagnostic intelligence as a strategic asset are likely to gain a significant advantage. By integrating predictive analytics into commercialization planning, pharmaceutical companies can validate market opportunities, prioritize physician outreach, and ultimately expand access to life-changing therapies.

"Predictive analytics transforms diagnostic data from a retrospective record into a prospective strategic tool," More said. "When pharmaceutical companies understand where patients are in the diagnostic journey, they can design launch strategies that reach the right physicians, support earlier diagnosis, and ensure therapies benefit the patients who need them most."

Healthcare organizations that leverage diagnostic intelligence as a strategic asset will be better positioned to validate market opportunities, prioritize outreach, and improve patient access to therapies.

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