We have published a new therapeutic-discovery case study focused on Alzheimer's disease through an amyloid-pathway hypothesis centered on BACE1. The campaign was run as a strict in-silico triage workflow, not as a clinical claim: root-cause target framing, anti-target control against AChE and KCNH2, and explicit CNS ADMET gates all had to hold at the same time.
The confirmed local reruns behind the published page finished in 23m 28s on a home PC. Across the broad discovery space, FluxMateria evaluated 707 candidates and returned 48 strict passes. The final shortlist did not collapse into a single lucky series either. Two independent BACE1-native chemotypes survived the full gate: lanabecestat-like and verubecestat-like families.
One of the most important points in this case study is methodological. FluxMateria was given a BACE1-centered amyloid brief and realistic constraints, but it was not explicitly told to reproduce those named historical pharma families. Those families emerged from the broad search, and only after that were focused refinement sweeps used to improve the chemistry. That makes the convergence more meaningful than a retrospective curve-fit.
The case study also makes the right scientific boundary explicit. FluxMateria already did the discovery, ranking, counter-screening, and prioritization work. The next step is experimental validation: confirm BACE1 activity, confirm selectivity and safety margins, and test whether the shortlisted molecules reduce amyloid-beta output in relevant assays.
If you want the full package, the public materials now include the full case-study page, a downloadable white paper, and a public JSON packet with the top-shortlist metrics and disclosed finalist structures.
This article describes an in-silico preclinical discovery workflow. It is not a diagnosis, treatment recommendation, or clinical efficacy claim.