Oncology drug development is time consuming, costly, and high risk, with rates of a successful outcome (FDA drug approval) being very low. This is a perfect problem area for Lantern Pharma’s approach to drug development involving machine learning, AI, and rapid, data-driven hypothesis testing using in vitro and in vivo models.
Success rate of cancer drugs in clinical trial testing
Cancer is the second leading cause of death after heart disease
Current global oncology drug market
Biomarker-based trials are 12 times more likely to succeed
Oncological clinical trials launched since 2007
Lantern Pharma’s pharmaceutical biotechnology solution is through the development of a process that accurately stratifies patient populations into responders and non-responders for a wide variety of oncology therapies to de-risk clinical trials, develop companion diagnostics and increase the potential for successful FDA approval with reduced costs.
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