PatientGPT replaces 6 months of drug research in seconds
Special focus on life science: large language model (technology like ChatGPT) based on supervised machine learning
With PatientGPT, Semalytix aims to usher in a new era in pharmacy. Thanks to the interfaces between supervised machine learning and large-language models, the PatientGPT prototype aims to achieve unprecedented data precision - a milestone for life science. Effects of drugs from millions of patient experiences can be analyzed and interpreted in seconds. This would otherwise have taken up to six months of work. Added to this is Europe's locational advantage: security and anonymization of sensitive patient data are subject to clear guidelines.
For almost eight years, the Bielefeld-based life science startup Semalytix has been changing the pharmaceutical market, which is worth over 1.25 trillion, and supplying key technologies made in Bielefeld. With the world's first working prototype of the PatientGPT, the company from East Westphalia is going one step further. "We can not only analyze the effects of any medication based on patient experiences around the world, but also specifically interrogate the smallest detail," says co-founder and Chief Product Officer Janik Jaskolski. "By the end of the year, we will have over 50 million patient experience data points that our proprietary GPT solution will have access to. This will allow us to know exactly how people live with diseases and provide fundamental new insights for patient-centered medicine development," says cognitive informaticist Janik Jaskolski.
The boundaries of what is possible are shifting
"PatientGPT takes chance out of random research and unleashes huge potential for groundbreaking new research in pharmaceuticals," says co-founder and Chief Technology Officer Prof. Philipp Cimiano. The most popular example from the near past is the accidental invention of the potency drug Viagra in 1998, actually just a side effect of the tested hypertension drug and misappropriated based on patient experience. A learning that can now be potentiated thanks to new technologies. "Based on over 100 million sources, in 26 different languages, bundling all patient experiences worldwide over the last ten years, the wealth of knowledge is already on our Pharos platform," says Janik Jaskolski.
The knowledge is made accessible by the synergy of the database and the large-language model. PatientGPT makes it possible that the answers are based exclusively on data that has already been analyzed by Semayltix' extensive AI framework.
Extremely accurate and free of hallucinations. The prototype can also access real-time data. "Billions of pieces of information about patient-centered experiences reveal entirely new therapeutic and medication opportunities," says Janik Jaskolski, adding, "What are the experiences of patients around the world with drug X and condition Y? PatientGPT aggregates thousands of patient voices and keeps providing answers to the questions - tirelessly, again and again."
The new PatientGPT puzzle piece for comprehensive AI-based research technology is saying hello to diseases like depression, breast cancer and diabetes. "We want to dramatically accelerate the pace of therapy and drug development. To do this, we are making global patient experience available while adhering to all ethical guidelines," says Chief Product Officer Janik Jaskolski. Initial case studies are also already proving the coming AI medicine revolution and underline the important work of the Bielefeld-based pioneers in this field. Semalytix customers include many of the top 20 pharmaceutical companies worldwide.
Note: This article has been translated using a computer system without human intervention. LUMITOS offers these automatic translations to present a wider range of current news. Since this article has been translated with automatic translation, it is possible that it contains errors in vocabulary, syntax or grammar. The original article in German can be found here.
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