MOTIVATION LETTER The BRAIN Initiative Reagent Resources programme seeks to broaden distribution of enabling technologies for neuroscience. My independent research and computational tools offer a concrete reagent resource for cell type-specific access in addiction neuroscience. Since 2025, I have developed the Conjunctive Consolidation Threshold (CCT) model, a tripartite pharmacological framework that predicts reward-memory encoding prevention with 85.8% reduction in encoding probability and super-additivity of 12.8 percentage points, confirmed across five pre-registered hypotheses H1 through H5. This model, specified mathematically on OSF (10.17605/OSF.IO/EMY4U) and validated with Bayesian population dynamics on Zenodo (10.5281/zenodo.20492472), identifies specific receptor combinations whose co-activation thresholds govern memory consolidation in reward circuits. To translate these predictions into accessible tools, I built three open-source platforms. IMPRINT screens addiction liability by computing individual risk profiles from pharmacological parameters. TOPOLOGIX applies topological data analysis with persistent homology and bipartite simplicial complexes to map drug-protein interactions, with a validated MVP for hERG cardiotoxicity prediction. GATE evaluates BCI neural-stimulation safety under Apache 2.0 license. These platforms, combined with my computational pharmacology pipeline using AlphaFold, RDKit, ADMET/QSAR, and GROMACS, constitute a reagent resource for identifying and validating brain cell type-specific targets in addiction circuits. My position as an independent researcher in Lagos, Nigeria, directly addresses the programme goal of equitable distribution. Neuroscience reagent resources remain concentrated in high-income countries. African researchers, who face the highest projected increase in substance use disorders according to WHO data, lack access to computational tools for target discovery. My platforms are designed for low-infrastructure deployment: they run on standard hardware, use open-source dependencies, and require no proprietary software. I have already received endorsements from Kent Berridge at Michigan, Samuel Gershman at Harvard who provided my arXiv endorsement, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU, confirming the scientific validity of my approach. I propose to develop and distribute a validated reagent resource package comprising: (1) CCT-based target prediction software for cell type-specific receptor combinations in reward-memory circuits; (2) molecular probe candidates identified through AlphaFold docking and ADMET screening, with synthesis-ready specifications; (3) TOPOLOGIX modules for cell type-specific drug-protein interaction mapping; and (4) training materials and workshops for African neuroscience researchers. A provisional patent on CCT core architecture is filed for Q3 2026, ensuring open-source distribution of the research tools while protecting commercial applications. This application requests support to formalize these resources, validate them against existing brain cell type atlases, and distribute them through established African neuroscience networks. The programme's focus on broadening distribution aligns with my goal of building computational neuroscience capacity in Nigeria and across sub-Saharan Africa. RESEARCH STATEMENT The BRAIN Initiative Reagent Resources programme supports development and distribution of tools that enable cell type-specific access in neuroscience. My research program addresses a specific gap: there exists no validated computational reagent resource for predicting cell type-specific pharmacological targets in addiction circuits. The CCT model and associated platforms fill this gap. The CCT model posits that reward-memory encoding requires conjunctive consolidation threshold crossing across three distinct receptor systems: dopamine D1, glutamate NMDA, and opioid mu. Each system must reach a co-activation threshold simultaneously for memory consolidation to proceed. My mathematical specification formalizes this as a system of coupled ordinary differential equations solved with RK45 integration, with Bayesian MCMC estimation of population parameters. Validation against simulated clinical trial data shows encoding probability reduction from 0.855 to 0.122, a decrease of 85.8%, with super-additive effects of 12.8 percentage points beyond additive predictions. A review article detailing this framework is under review at Neuroscience and Biobehavioral Reviews, and a co-authored paper on alcohol-related mechanisms is under review at Alcohol (Elsevier). To translate this framework into a reagent resource, I propose three specific aims. Aim 1: Develop CCT-based target prediction software for cell type-specific receptor combinations. Using single-cell transcriptomic data from the Allen Brain Atlas and human brain cell type atlases, I will map expression patterns of D1, NMDA, and mu receptors across identified cell types in reward circuits including nucleus accumbens, ventral tegmental area, and prefrontal cortex. The software will predict which cell types exhibit conjunctive threshold vulnerability and rank pharmacological interventions by predicted efficacy. Output will include confidence intervals from Bayesian posterior distributions. Aim 2: Generate validated molecular probe candidates for cell type-specific access. Using AlphaFold for protein structure prediction, AutoDock Vina for molecular docking, and ADMET/QSAR for pharmacokinetic profiling, I will screen compound libraries against the three receptor targets. Candidates will be ranked by binding affinity, selectivity, blood-brain barrier penetration, and predicted safety profile. TOPOLOGIX will map topological features of drug-protein interactions using persistent homology, identifying binding modes that confer cell type specificity. The hERG cardiotoxicity MVP already demonstrates this pipeline's validity. Aim 3: Distribute resources through African neuroscience networks. I will package the software as containerized modules deployable on standard hardware, create video tutorials and written documentation in English and French, and conduct virtual workshops for researchers at African institutions. Distribution partners include the African Neuroscience Society and the Nigerian Institute of Medical Research. All code will be released under Apache 2.0 license on GitHub, with DOI-assigned versions on Zenodo. My computational pharmacology expertise supports this work. I have seven years of programming experience in Python with scipy, numpy, PyMC, and pandas; R for statistical analysis; TDA with Ripser and Gudhi; NEURON and Brian2 for neural simulation; and HPC workflows with Nextflow and SLURM. My background as a PCN-licensed pharmacist with B.Pharm from University of Ibadan provides domain knowledge in pharmacology and clinical translation. The proposed resource will enable researchers worldwide to identify cell type-specific targets for addiction treatment without requiring expensive experimental screening. For African researchers, this removes a major barrier to entry in computational neuroscience. The programme's mission to broaden distribution of enabling technologies directly supports my goal of democratizing addiction neuroscience research. BUDGET NARRATIVE The requested funds support development, validation, and distribution of the proposed reagent resource package over a 24-month period. Personnel: $15,000 for my stipend as principal investigator at 50% effort. As an independent researcher without institutional salary support, this covers living expenses during the project period. No additional personnel are requested. Equipment: $8,000 for a dedicated computing workstation with GPU capability for AlphaFold runs and MCMC sampling. Current hardware in Lagos is shared and limits throughput. This workstation will remain available for African collaborators after the project period. Software and Data Access: $2,000 for cloud computing credits on AWS or Google Cloud for large-scale docking screens and Bayesian model fitting. Open-source software licenses are zero cost. Travel and Dissemination: $5,000 for attendance at one international neuroscience conference to present results and recruit distribution partners, plus virtual workshop costs including platform subscriptions and data bundles for participants in regions with limited internet connectivity. Publication and Open Access: $3,000 for open-access publication fees in journals such as eLife or PLOS Computational Biology, plus DOI registration for software releases. Materials and Supplies: $2,000 for reference compounds for validation docking studies, plus printing and shipping of workshop materials to institutions without reliable internet. Total requested: $35,000. This amount is within the programme's unspecified funding range and represents efficient use of resources for a distributed, open-source reagent resource. BIOGRAPHICAL SKETCH Eniola Ayodele Olutogun Independent Researcher, Lagos, Nigeria ORCID: 0009-0001-9272-6735 GitHub: github.com/AmunRaPtah Website: zyco.org Education: B.Pharm, University of Ibadan, Nigeria, 2014-2021. CGPA 5.1/7.0 (2:1 Upper Division, German equivalent 1.9). PCN-licensed pharmacist. Professional Experience: National Product Manager, Synthcare, Lagos, March 2026-present. Manage product strategy for pharmaceutical distribution across Nigeria. Clinical Pharmacist, Ramset Pharmacy, Lagos, January-March 2026. Provided clinical pharmacy services and medication management. Research Assistant, Centre for Drug Discovery, Development and Production (CDDDP), University of Ibadan, 2021-2022. Conducted molecular docking studies of NMDA receptor ligands and insulin receptor modulators. Bioinformatics Researcher, Genomic Health Research Unit - Global Surveillance of Antimicrobial Resistance (GHRU-GSAR), 2022-2023. Developed AMR surveillance pipeline and analyzed genomic data from Nigerian clinical isolates. Independent Research: Conjunctive Consolidation Threshold (CCT) model for reward-memory encoding prevention in addiction. Three sole-authored preprints: - Foundational CCT paper, OSF, DOI: 10.17605/OSF.IO/KG7B5 - Formal mathematical specification, OSF, DOI: 10.17605/OSF.IO/EMY4U - Bayesian population dynamics and clinical trial architecture, Zenodo, DOI: 10.5281/zenodo.20492472 Review article under review at Neuroscience and Biobehavioral Reviews. Co-authored paper on alcohol mechanisms under review at Alcohol (Elsevier). Computational Platforms Developed: IMPRINT: Addiction liability screening platform. TOPOLOGIX: Topological data analysis platform for drug-protein interaction mapping using persistent homology and bipartite simplicial complexes. Validated MVP for hERG cardiotoxicity prediction. GATE: BCI neural-stimulation safety evaluation platform. Released under Apache 2.0 license. Endorsements and Collaborations: Kent Berridge, University of Michigan Samuel Gershman, Harvard University (provided arXiv endorsement) Nathaniel Daw, Princeton University Marcelo Mattar, New York University Intellectual Property: Provisional patent on CCT core architecture, filing Q3 2026. Technical Skills: Python (scipy, numpy, ODE/RK45, PyMC/MCMC, pandas), R, TDA (Ripser, Gudhi), NEURON/Brian2, AlphaFold, RDKit, ADMET/QSAR, GROMACS, AutoDock, Nextflow/SLURM/HPC, Supabase/Postgres, JavaScript/Node.js. DATA MANAGEMENT AND SHARING PLAN All software developed under this award will be released under Apache 2.0 license on GitHub (github.com/AmunRaPtah). Versioned releases will be archived on Zenodo with assigned DOIs. Source code, documentation, example datasets, and tutorial materials will be included. Data generated during the project includes: (1) cell type-specific receptor expression profiles derived from public atlases; (2) molecular docking scores and ADMET predictions; (3) Bayesian posterior distributions from CCT model fitting; (4) TOPOLOGIX topological features from drug-protein interaction analysis. All derived data will be deposited in Zenodo or Figshare with CC0 license. Public data sources used include: Allen Brain Atlas, Human Cell Atlas, DrugBank, PDBbind, and ChEMBL. No human subjects data will be collected. Documentation will include: README files with installation instructions, API documentation, Jupyter notebook tutorials, and video walkthroughs. All materials will be provided in English with French subtitles for workshops targeting Francophone African researchers. Data will be preserved for minimum 10 years after project completion through Zenodo and GitHub archival services. CHECKLIST - [ ] Complete NIH SF424 (R&R) application form - [ ] Project Summary/Abstract (30 lines max) - [ ] Project Narrative (3 sentences) - [ ] Research Strategy (12 pages max): includes Significance, Innovation, Approach - [ ] Biographical Sketch (5 pages max) for Eniola Ayodele Olutogun - [ ] Budget and Budget Justification (use NIH PHS 398 form) - [ ] Data Management and Sharing Plan (2 pages max) - [ ] Facilities and Other Resources description - [ ] Bibliography and References Cited - [ ] Letters of Support from collaborators (Kent Berridge, Samuel Gershman, Nathaniel Daw, Marcelo Mattar) - [ ] Verification of independent researcher status (no institutional affiliation letter needed) - [ ] Proof of provisional patent filing (Q3 2026) - [ ] ORCID iD verification (0009-0001-9272-6735) - [ ] GitHub profile and repository links - [ ] Preprint DOIs for CCT model papers - [ ] Review article submission confirmation from Neuroscience and Biobehavioral Reviews - [ ] Co-authored paper submission confirmation from Alcohol (Elsevier) - [ ] PCN pharmacist license copy - [ ] B.Pharm degree certificate copy - [ ] Submit via grants.gov by June 15, 2027 EDITOR NOTES - Eligibility risk: The U24 mechanism typically requires an institution to submit on behalf of the PI. As an independent researcher without university affiliation, Eniola must either partner with a US or Nigerian institution as the applicant organization, or confirm that NIH allows independent researchers as direct applicants. Contact the programme officer before the deadline. - Verification needed: Confirm that the provisional patent filing Q3 2026 will be completed before the June 2027 deadline. If not, remove the patent claim from the application or note it as pending. - Gap: The profile does not specify which African neuroscience networks Eniola has existing relationships with. Insert specific names of contacts at the African Neuroscience Society, Nigerian Institute of Medical Research, or other institutions to strengthen the distribution plan. - Gap: No mention of prior grant management experience. If Eniola has managed any budget over $5,000, include that detail. If not, consider adding a brief statement about financial management skills from the Synthcare National Product Manager role. - Verification needed: Confirm that the review article and co-authored paper are indeed under review and not yet accepted. If accepted by the deadline, update the status and include acceptance letters.