Addressing the 58% Launch Failure Rate: Accelerating Market Access Through Intelligent Decision-Making
Here are some of the structural and strategic causes behind that failure rate, and ways to improve launch outcomes.
Here are some of the structural and strategic causes behind that failure rate, and ways to improve launch outcomes.
When applied with a rigorous, subject-matter-expert guided process, AI-currated RWD is an essential resource giving life science organizations new power to monitor the diverse variety of ways drugs are actually utilized post-approval.
Some specialties, like oncology, have been quicker to embrace the promise of pharmacogenomics (PGx), and their successes can serve as a roadmap as others explore the impact it can have on quality, outcomes and patient satisfaction.
Personalized and highly-targeted therapeutics are becoming more common, making local or regional production increasingly valuable for faster patient access. This underscores how a hybrid network combining large, centralized plants coupled with flexible regional sites will define the next era of resilient biomanufacturing.
As RWE continues to influence the future of drug development, pharma companies will inevitably encounter hurdles. But with the right approach, they can be overcome to unlock critical insights and bring better therapies to patients faster.
It reduced cravings, dulled alcohol’s “buzz,” and carried no risk of addiction. By every measure, naltrexone should have immediately become a major triumph. Instead, it flopped because the institutions charged with treating addiction refused to use it. Now considered a gold standard, it survived because patients and communities kept it alive.
This year will be the turning point from AI “hype” to the adoption of meaningful AI and digital health solutions in pharma. Here four predictions.
Those who act first will lower cost to serve, boost rep productivity and deliver customer experiences that feel personal, not programmatic. Those who wait risk falling behind as competitors turn engagement into a true differentiator.
The same forces now at play in medical aesthetics will soon appear in every therapeutic category where treatment overlaps with identity, from hormones to nootropics to genetic optimization.
New tools can predict deadly reactions to common cancer drugs, but adoption lags despite evidence.
In a landscape where complexity has long been the norm, the power of one lies not just in unification, but in intelligence and automation.
The technology already exists that would allow us to close the loop between physiological dysfunction and neural adaptation in real time. The question is not if, but how, rapidly this capability will reshape therapeutic paradigms and the economics that sustain them.
The growing use of advanced analytics and artificial intelligence (AI) is reshaping this landscape by enabling data-driven process control, predictive manufacturing, and greater transparency across the development lifecycle.
We urgently need biomarkers that are sensitive, objective, and practical. Eye-movement measures are ready to fill this gap, not as distant innovations, but as tools available today.
Genomic technologies not only help to identify cancers, but also offer opportunities for assessing the potential efficacy of different treatment options. By analyzing the genomic profile of a particular patient, doctors can see which medications might offer the most support, and which could cause more harm.
Antibiotic resistance is a growing global threat with serious health and economic consequences. Yet there is progress – from rapid PCR diagnostics and AI-driven research to new drug development and innovative funding models.