A new manuscript has been published on MedRxiv titled “Machine learning applied to clinical laboratory data predicts patient-specific, near-term relapse in patients in medication for opioid use disorder treatment”. Reporting positive data from a clinical study, this paper demonstrates the power of data-driven predictive analytics in precision psychiatry, specifically in predicting relapse in opioid addiction, one of the programs being pursued by Altimate Health, an Iaso Ventures portfolio company. The paper’s first author is Altimate’s CEO Paul Pyzowski and senior author is Wasim Malik. The abstract is below and the full paper can be accessed here.

We have developed a data-driven, algorithmic method for identifying patients in an out-patient buprenorphine program at high risk for relapse in the following seven days. This method uses data already available in clinical laboratory data, can be made available in a timely matter, and is easily understandable and actionable by clinicians. Use of this method could significantly reduce the rate of relapse in addiction treatment programs by targeting interventions at those patients most at risk for near term relapse.