by Margaretta Colangelo
Leading AI Analyst Tracking AI Milestones in Healthcare
Medical Records in a New Light: A Patient’s Own Experience
“PatientGPT produces clear summaries of patients’ experiences in dozens of disease areas.”
What if you could watch every online TikTok—as well as read scads of other non-standard, online medical information—made by, say, diabetic patients about living and coping with their disease? Might well be a new trove of insights about diabetes from the very people who contend with it daily. Maybe, as well, a few new insights on novel approaches to the disease and a few hints at new therapeutics.
That’s the idea behind Semalytix’s mission. Valuable disease information from non-standard sources.
“We don’t analyze physician or hospital data. Instead, we are looking at already existing public data that patients share online, in their own authentic voice, all around the world.” The largest source of unstructured patient data that exists today is being overlooked and yet holds a lot of potential to “improve patient care, identify new therapeutic opportunities, inform clinical trial development and even help accelerate development of novel therapies for rare conditions.” —Janik Jaskolski, Chief Product Officer and co-founder Semalytix
Founder and CEO,
Margaretta Colangelo Ventures
of Pharma Research
Large language models are as profound an innovation as the computer mouse. Just as the mouse makes it possible for humans to interact with computers in an intuitive way, LLMs make it possible for humans to interact with AI using natural language. Scientists are beginning to develop practical applications using this powerful technology.
This month German AI company Semalytix launched a new patient-centric generative AI tool called PatientGPT™.
This new tool is able to recognize, summarize, and translate patients’ own words about quality-of-life, symptoms experienced, medication side effects, treatment experiences, and unmet needs.
Semalytix collects real world patient data and uses a branch of AI called natural language processing to identify unrecognized issues associated with a disease. This tool generates multidimensional insights from millions of patients instantly, reducing months of research into a few seconds. These insights can help pharmaceutical companies accelerate research, de-risk clinical trial design, and improve patient outcomes. This is a milestone for AI in healthcare.
PatientGPT is exclusively tuned to supervised patient experience data and always acts with conceptual disease models in the background.
Semalytix has collected over 50 million patient experience statements in 26 languages to make the world’s largest real-time patient experience data stream.
Using powerful AI algorithms to interpret it, combined with a proprietary analytics platform, PatientGPT produces clear summaries of patients’ experiences in dozens of disease areas. Semalytix’s AI platform has already successfully been used to generate evidence and patient insights for Crohn’s disease, breast cancer, psoriasis, obesity, ulcerative colitis, melanoma, lupus, and diabetes, and the company’s pipeline includes 25 additional indications. Several top pharma companies are already using the platform.
Generating synthetic patients with global disease memory
There’s huge potential to use PatientGPT technology to generate synthetic patients with global disease memory. PatientGPT has a ChatGPT-style interface that has been exclusively tuned to supervised patient experience data. These synthetic patients can be interviewed interactively or answer questions in batch mode. This novel way of extracting and condensing information from a massive dataset has only recently become possible due to advances in AI. By restricting the training set to specific cohorts of patients, the synthetic patient may be configured to assist with exploring particular questions of interest that match specific demographic variables. This can help drug developers identify new clinical endpoints and massively scale how they achieve real-world value for patients.
“Since most AI companies analyze data from electronic health records and patient registries, the largest source of unstructured patient data is being overlooked. Semalytix has collected over 50 million patient experiences and has the world’s largest real-time patient experience data stream. This data holds huge potential to address patient needs, discover new markets for existing drugs, identify new therapeutic opportunities, inform future clinical trial development, and even help accelerate the development of novel therapies for rare conditions. PatientGPT can interrogate, analyze and interpret this data in a matter of seconds. We are really excited by the possibilities”
Using AI to extract and condense massive datasets
Over the last 20 years people on blogs, forums, and social media have compiled the world’s largest patient experience dataset. Health ranks among the top 5 topics discussed on social media and over 50% of patients and families share their health experiences online. However, most pharma companies don’t collect this data and lack sophisticated tools to create consistent value from it. Most AI companies that focus on real-world evidence, collect data from electronic health records in hospitals.
Since 2015 Semalytix has been collecting public data that people share on blogs, forums, and social media about their experiences living with diseases and taking medications. The data sets that Semalytix collects contain different types of information than found in electronic health records. Since patients don’t report all of their side effects and experiences to their doctors, electronic health records are incomplete and don’t provide an accurate picture of a patient’s daily life. Without access to authentic patient-experiences, pharma companies risk spending years developing treatments that don’t address the true needs of patients.