Mission statement
The mission of OpAIx is to support surgeons in reducing or eliminating excess opioid prescribing at hospital discharge through innovative models that estimate each patient's individual needs.
Founded in Pittsburgh by UPMC physicians and AI researchers.
Patients leaving the hospital may receive more opioid pills than they need. Unused medication can create opportunities for misuse, accidental exposure, and diversion within households and the wider community.
Medication take-back programs aim to reduce this surplus, but collecting unused pills addresses the problem after they have already been prescribed.
OpAIx focuses on the prescribing decision itself: helping surgeons estimate how many opioid pills an individual patient may need after discharge. The goal is to support appropriate pain management while minimizing leftover medication and the risk of diversion.
Opioid needs after discharge depend on more than pain alone. OpAIx's approach considers the patient's clinical context, treatment history, and recovery to support a more individualized estimate.
How pain is expected to change throughout recovery.
The procedure and its associated recovery needs.
The individual’s medical background and relevant family history.
The patient’s history of opioid use before the procedure.
The amount of opioid medication used during the hospital stay.
Guidance on which medication to take at different levels of pain.
The broader treatment plan, including non-opioid strategies.
Pain matters. Individual needs go further.
Severe postoperative pain can interfere with recovery, including a patient's ability to regain function. Reducing pain is important, but pain alone does not determine how many opioid pills a patient may need after leaving the hospital.
OpAIx was founded to help surgeons make more individualized prescribing decisions by considering expected pain alongside the other factors that shape opioid needs. Our goal is to support recovery while minimizing unused pills after discharge.
Developed in Pittsburgh, OpAIx draws on the research experience of Co-Founder and CMO Dr. Jacques Chelly. He brings more than 30 years of clinical research experience, including work at the University of Pittsburgh since 2002, exploring postoperative opioid needs and alternatives to opioids in acute perioperative care.
Selected peer-reviewed work in perioperative pain that includes publications co-authored by co-founder Dr. Jacques Chelly. Titles link to the publisher record; brief summaries below are written for this site and are not taken from the articles. They describe clinical context only and do not validate OpAIx models.
Narrative review of acute pain biology, opioid prescribing considerations, and multimodal analgesia. Useful background on why discharge prescribing is often discussed alongside non-opioid strategies.
Why pain
Describes study design for genetic analyses of acute and persistent pain after knee replacement. Highlights patient-level variation beyond average pain scores in perioperative research.
Predicting pain
Discusses combining patient-reported pain with opioid consumption when judging analgesic effect in trials. Relevant to outcome measurement when pain alone does not capture medication use.
Measuring outcomes
Review of perioperative low-dose ketamine regimens and reported analgesic effects. Context for opioid-sparing options in acute postoperative care.
Opioid-sparing care
Reports lower post-discharge opioid prescribing after a structured behavioral intervention in urologic surgery. An independent research result, not an OpAIx product outcome.
Opioid-sparing care
Clinical study linking continuous femoral nerve blockade to recovery measures after total knee arthroplasty. Example of regional analgesia affecting function, not only pain scores.
Earlier intervention
Large randomized trial comparing anesthesia techniques for hip fracture surgery on pain, analgesic use, and satisfaction. Illustrates rigorous measurement of perioperative patient-reported outcomes.
Measuring outcomes
Retrospective analysis of low-dose peripheral nerve blocks and postoperative analgesia and mobility after knee replacement. Adds real-world context on blocks and functional recovery.
Measuring outcomes
Co-Founder & CEO
Focused on building AI tools that make clinicians more effective and elevate the accuracy and speed of patient care. She turns complex data and machine-learning research into solutions clinicians can actually use, improving decision-making, streamlining diagnostics, and enabling better outcomes at scale.
Co-Founder & CMO
Anesthesiology, University of Pittsburgh
Dr. Chelly has over 30 years of clinical research. Since 2002 he has led the University of Pittsburgh’s anesthesiology clinical research program, which has enrolled thousands of subjects. Author of Peripheral Nerve Blocks: A Color Atlas (Lippincott Williams & Wilkins) and holder of patents in regional anesthesia delivery.
CPO AI & ML
AI & ML product leader with two decades of building and scaling data-driven products. Specialized in transforming complex machine-learning research into commercially successful, user-centric solutions. Known for shipping fast, aligning cross-functional teams, and driving measurable business impact across enterprise and consumer platforms.
Work that involves protected health information is designed to sit inside a health system’s HIPAA programme. Data used to develop or evaluate models is de-identified where the research protocol allows. This is not a certification badge.
When academic partners contribute clinical research data, it is used only under that institution’s IRB-approved protocol and the agreements that come with it.
Access to systems that hold clinical data is limited to named people, authenticated, and logged. Details of hosting and controls are shared with health-system partners under NDA.
Surgeons, CMIOs, anesthesiology and peri-operative chiefs, health-system innovation teams, clinical research partners, and seed investors should write. We will say plainly where the models are in validation and what a collaboration would take.