INmune Bio Becomes Quantum Computing Inc.'s First Pharma Customer on 14 October 2026: What Dirac-3S Will Search for in the XPro Alzheimer's Trial Data
INmune Bio puts XPro trial data on a quantum optimizer
Quentir Medicine Monitor
Evidence-based insights for quantum medicine.
On 14 October 2026 the Alzheimer's drug developer INmune Bio and the photonics company Quantum Computing Inc. (QCi) announced that INmune Bio will use QCi's Dirac-3S quantum optimization machine to look for new diseases in which its anti-inflammatory candidate drug might work. The engagement is a first stage with options for more, and QCi describes it as its first commercial customer in the pharmaceutical and biotechnology market.
The drug is XPro1595, which INmune Bio calls XPro. It is designed to neutralize the soluble form of tumor necrosis factor, a signaling protein that drives inflammation, while leaving the membrane-bound form, which the immune system and nerve cells rely on, largely untouched. INmune Bio has tested it in early Alzheimer's disease in patients whose blood shows signs of inflammation.
According to the joint announcement issued from Boca Raton and Hoboken, the two companies will combine INmune Bio's data from preclinical work and four clinical trials with public biomedical datasets. The aim is to find new indications, meaning diseases driven by the same inflammatory biology XPro targets, and to rank them by their chance of success. INmune Bio's chief executive David Moss said the search would start with rare diseases, where trials can be smaller and faster, and where a qualifying pediatric approval may earn a priority review voucher from the US Food and Drug Administration.
The announcement contains one commitment that deserves more attention than the headline. The companies say they will compare the quantum machine's output with conventional statistical and machine-learning methods and judge which approach suits which part of the analysis. Whether that comparison is published will decide how much the collaboration teaches anyone outside the two companies.
The largest body of patient data INmune Bio brings to the work comes from MINDFuL, a randomized, double-blind, placebo-controlled phase 2 trial registered as NCT05318976 on ClinicalTrials.gov. The registry lists 207 enrolled participants, a start in February 2022 and completion on 12 May 2025. Patients aged 50 to 85 with mild cognitive impairment or mild dementia and raised inflammatory biomarkers received a weekly injection under the skin of XPro1595 at 1.0 mg/kg or a placebo for 24 weeks, at 35 centers in eight countries.
The results, written up by Judith Jaeger, Christopher Barnum and colleagues in a preprint posted to medRxiv on 27 September 2025, are mixed. In the 200 patients of the modified intent-to-treat population, the drug did not beat placebo on the primary endpoint, a composite of six cognitive tests called the Early and Mild Alzheimer's Cognitive Composite (EMACC), with p = 0.672. The authors write plainly that XPro1595 did not meet the primary endpoint in the overall population.
Simulated Quantum Annealing Ranked Known Drug Pairs First for Diabetes and Rheumatoid Arthritis: Ramos, Coutinho and Magano in Quantum Machine Intelligence, 23 June 2026
Quentir Medicine Monitor
Evidence-based insights for quantum medicine.
Three researchers from Porto and the German Aerospace Center have written drug-pair selection as an energy problem that a quantum annealer could solve, and tested it on diabetes, rheumatoid arthritis, asthma and brain tumors. In simulation, the lowest-energy answers were dominated by drug combinations that doctors already use, and one of the top new suggestions for rheumatoid arthritis matches a pairing that a 799-patient trial found to roughly double remission rates.
The paper, by Diogo Ramos, Bruno Coutinho and Duarte Magano, appeared open access in Quantum Machine Intelligence on 23 June 2026 as article 70 of volume 8. It builds on the Complementary Exposure idea from network medicine, turns it into an optimization problem, and samples answers with simulated quantum annealing, a classical computer program that imitates how quantum annealing hardware behaves. Its central test is how often validated drug combinations appear among the top-ranked answers when they make up less than a tenth of a percent of the candidates.
Combination therapy is standard across chronic disease and oncology, because two drugs together can allow lower doses and fewer side effects. The search space is the problem. With more than a thousand approved drugs and thousands of diseases, the number of possible pairs grows far faster than any laboratory or trial program can test them.
For a pharmacology team or a hospital formulary committee, the study offers a clear example of what quantum optimization can and cannot yet contribute to that search. The ranking method works in simulation on four diseases. No quantum computer was used, and the authors state plainly that their predictions are hypotheses for experts to examine.