Albert Einstein College of Medicine

Studies at the 66th ASH Annual Meeting highlight progress in preventing and treating blood cancers, including daratumumab reducing disease progression risk by half in high-risk multiple myeloma patients, acalabrutinib and venetoclax combination improving progression-free survival in untreated CLL patients, epcoritamab showing promise in relapsed/refractory CLL, genetic changes and elevated leukemia risk in Ground Zero first responders, and socioeconomic factors limiting access to stem cell transplants for AML patients.

The ENCORE trial showed AXS-12, an investigational narcolepsy treatment, significantly reduced cataplexy attacks and improved daytime sleepiness, cognition, and productivity. Axsome plans to file an NDA for AXS-12 and request a pre-NDA meeting with the FDA.

Axsome Therapeutics' reboxetine (AXS-12) met primary endpoint in phase 3 ENCORE trial, significantly reducing cataplexy attacks in narcolepsy patients compared to placebo. Long-term dosing showed sustained improvements in cataplexy, excessive daytime sleepiness, cognition, and overall function, with a favorable safety profile.

NIH researchers developed TrialGPT, an AI framework using large language models to streamline clinical trial matching on ClinicalTrials.gov, achieving nearly the same accuracy as human clinicians. TrialGPT analyzes patient summaries to identify eligible trials, reducing clinician screening time by 40% while maintaining accuracy. The tool relies on OpenAI’s GPT-3.5 and GPT-4 models and will be further assessed for performance and fairness in real-world settings.

AXS-12 significantly reduced cataplexy attacks, improved cognition, and overall narcolepsy symptoms compared to placebo in the ENCORE Phase 3 trial. Patients experienced substantial reductions in cataplexy and excessive daytime sleepiness, with sustained improvements in cognition and overall function. AXS-12 was well-tolerated with a safety profile consistent with previous trials.

Axsome Therapeutics announces AXS-12 (reboxetine) achieved primary endpoint in ENCORE Phase 3 trial for narcolepsy, showing significant reduction in cataplexy attacks and improved safety profile.

NIH developed TrialGPT, an AI algorithm matching potential volunteers to relevant clinical trials on ClinicalTrials.gov, aiding clinicians in navigating trial options efficiently. TrialGPT processes patient summaries, identifies eligible trials, and explains eligibility criteria, reducing clinician screening time by 40% while maintaining accuracy. The tool aims to improve clinical trial enrollment and accelerate medical research progress.

Developing a precision approach to anesthetic/analgesic immunomodulation in cancer, exploring biomarkers (TMB, FGA) predictive of immunotherapy response and resistance. Analyzing drug effects on survival and recurrence in lung and colon adenocarcinoma patients, correlating drug target receptor gene expression with TMB, FGA, and immune cell types. Suggesting TMB and FGA as predictive biomarkers for anesthetic/analgesic dose effects on cancer patient survival.

NIH developed AI algorithm TrialGPT to match volunteers to relevant clinical trials on ClinicalTrials.gov, streamlining the process and improving enrollment. TrialGPT uses large language models to process patient summaries, identify eligible trials, and explain eligibility criteria, achieving nearly the same accuracy as human clinicians while saving time. The tool aims to enhance clinical trial recruitment and reduce barriers for underrepresented populations.

NIH introduces TrialGPT, an AI algorithm matching patients to clinical trials on ClinicalTrials.gov, aiming to accelerate research and improve enrollment. Developed by NIH's NLM and NCI, TrialGPT uses LLMs to process patient data, exclude ineligible trials, and rank eligible studies. It achieved near-human accuracy in a benchmarking study and demonstrated potential to save clinicians 40% of screening time.