Artificial Intelligence in Pharmaceutical Device Development

13 million patient records, millions of preclinical screening data points, and billions upon billions of recorded chemical structural connections: the sheer amount of data available gives us the ability to propel world health and medical development at an exponential rate. The issue is, however, that much of this data is relayed in unstructured, raw, or inaccessible formats, often trapped in patents, clinical records, or other documents. Therefore, the necessary bridge between drug development and future medicine is artificial intelligence. Today, machine learning in pharmaceutical device development shifts through biomedical data more efficiently in order to create a reliable and predictable blueprint for the entire cycle of preclinical and translational development for new drugs.

Reliability, efficiency, and personalization are the three keys to penetrating the pharmaceutical market. AI is the newest investment across all pharmaceutical companies, specifically in early-stage discovery and developmental phases. By bringing together biodegradability, contraception, and a focus on expanding medical accessibility across the world, Hera Health Solution’s flagship product, Eucontra, hits all the marks. Many of the developing algorithms in machine learning work to find new and innovative uses for the already 4,000+ FDA-approved drugs. As Hera Health expands to new products and markets, it is a possibility that AI could play a role in Hera Health Solution’s innovative process in the future.

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