Unlearn
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Description:
Unlearn is a company that uses artificial intelligence (AI) to power the future of medicine. Their mission is to solve AI for medicine and they are doing this by creating digital twins of patients. A patient’s digital twin is a comprehensive forecast of their future health. Unlearn invents and deploys new types of generative models trained on extensive patient-level data from previous studies. A participant's baseline data is collected and run through their AI model trained on historical data to create a digital twin of the participant.
Unlearn's digital twins are used to enhance clinical trials. They calculate prognostic scores for each patient in a randomized clinical trial using their digital twins. Adjusting for these scores in the analysis increases power while adhering to guidance from the US Food and Drug Administration and European Medicines Agency. TwinRCTs, which are highly powered trials with smaller control groups, use participants’ digital twins.
Unlearn is working in neuroscience, immunology, metabolic disease, and more. They are currently working on projects related to Alzheimer’s disease, amyotrophic lateral sclerosis, asthma, atopic dermatitis, COPD, coronary artery disease, Crohn’s disease, dyslipidemia, frontotemporal dementia, Huntington’s disease, hypertension, migraine, obesity, osteoarthritis, osteoporosis, Parkinson’s disease, psoriasis, psoriatic arthritis, rheumatoid arthritis, SCI, stroke, type 2 diabetes, and ulcerative colitis.
Unlearn is a leader in the field of AI for medicine. Their team of experienced scientists and engineers is dedicated to developing innovative solutions to improve the lives of patients.
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For Jobs:
Features
- Create digital twins of patients
- Calculate prognostic scores for patients in clinical trials
- Increase power in clinical trials
- Reduce the number of patients needed in clinical trials
- Improve the ability to observe treatment effects in early stage studies
Advantages
- Shorter time to enrollment in late stage studies
- More confident decisions from early stage studies
- Increased ability to attract study participants
- Smaller control groups in clinical trials
- Improved patient outcomes
Disadvantages
- Can be expensive to create digital twins
- Requires a lot of data to train AI models
- May not be able to predict all patient outcomes
Frequently Asked Questions
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Q:What are digital twins?
A:A patient’s digital twin is a comprehensive forecast of their future health. We invent and deploy new types of generative models trained on extensive patient-level data from previous studies. -
Q:How do digital twins enhance clinical trials?
A:We calculate prognostic scores for each patient in a randomized clinical trial using their digital twins. Adjusting for these scores in the analysis increases power while adhering to guidance from the US Food and Drug Administration and European Medicines Agency. -
Q:What are the benefits of using digital twins in clinical trials?
A:Digital twins can help to shorten the time to enrollment in late stage studies, make more confident decisions from early stage studies, attract more study participants, and use smaller control groups in clinical trials.
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