Life sciences and healthcare companies that set out to pioneer treatments in rare and specialty disease face a unique set of challenges. Typical pitfalls for advancing an indication in this space...
Nitin Choudhary, Managing Principal of IPM.ai and Richard Wilson, Rare Disease Franchise Head for Kyowa Kirin recently spoke on overcoming patient-finding challenges through machine learning (ML)...
Conventional clinical study recruitment methods for rare diseases simply don’t work. Analyzing ICD-10 and prescription data to determine patient clusters, site selection and feasibility is...
San Francisco – Aug. 19, 2021 – Real Chemistry’s IPM.ai, the leader in uncovering undiagnosed and misdiagnosed patients via machine learning, and Datavant, the leader in helping healthcare and...
Allison Rhee of MM&M reports on IPM.ai's answer to patient finding for rare and specialty diseases through advanced AI/ML. Read the full text below:
The rare disease patient journey can be arduous. Many patients experience multiple misdiagnoses or go undiagnosed before finally figuring out their true health issue and receiving treatment. For...
Targeted Approach Optimizes Clinical Study Recruitment of Medically-Eligible Patients Affected by Rare Diseases
Challenges are an inevitability when building a drug portfolio in the rare disease space, and patient finding is no doubt chief among them. Clinical trial recruitment is highly capital intensive,...
Though it’s not often discussed, often the most difficult aspect of bringing a drug to market is finding the right patient population. This is especially true with rare diseases, where patients...
Our own Julie Gubitosa and Graham Jones accompanied by Keith R. McCrae, MD of the Cleveland Clinic and Jennifer Beachell, Tricia Gooljarsingh PhD and Mary Lee Tjoa of Momenta Pharmaceutical,...
Leveraging the power of AI and RWD to identify, engage and activate ideal patient populations that could benefit from new therapies and modalities of care.
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