Eniola's strongest angle is the 'Artificial intelligence in cell culture media and process development' track (€150,000/yr × 3 years), repositioning IMPRINT and TOPOLOGIX as AI-driven CNS compound-liability screening tools embedded in a drug discovery process pipeline — directly relevant to Merck's Life Science Discovery Solutions division, which sells screening reagents and assay kits to pharma. The pitch should centre on TOPOLOGIX's persistent-homology / bipartite-simplicial-complex architecture for hERG cardiotoxicity prediction as a process-gate tool (early-phase CNS drug liability flagging before expensive wet-lab assays), and on IMPRINT's addiction-liability screening as an AI layer over Merck's cell-based assay workflow — with the CCT ODE/Bayesian results (85.8% encoding-reduction, all H1–H5 pre-registered hypotheses confirmed) as the mechanistic validation anchor. The endorsements from Berridge, Gershman, Daw, and Mattar should be named explicitly in the Stage 1 proposal to offset the ZYCO-vs-traditional-academic-institution gap; the ORCID, OSF pre-registrations, and under-review Elsevier paper all serve as substitute indicators of research rigour. Eniola should apply to a second track simultaneously — the neuroinflammatory diseases category — framing the CCT model's microglia-neuroinflammation-addiction nexus (neuroinflammation is a known co-morbidity in substance-use disorders) and proposing an in-silico screening layer to guide iPSC model design, positioning herself as a computational partner for a wet-lab collaborator rather than a standalone applicant.