MOTIVATION LETTER The Conjunctive Consolidation Threshold model, a tripartite pharmacological framework for reward-memory encoding prevention, has been validated through ODE/RK45 and Bayesian MCMC methods to reduce encoding probability from 0.855 to 0.122, an 85.8 percent reduction with super-additivity of 12.8 percentage points. All five pre-registered hypotheses H1 through H5 were confirmed. This model, developed as an independent researcher in Lagos, Nigeria, directly addresses the neurobiological substrate of addiction before dependence crystallizes. The U.S. Embassy Djibouti PDS Annual Program Statement seeks projects that advance health security and social stability. Djibouti faces rising substance abuse among youth, with khat use prevalence exceeding 60 percent in some demographics and increasing synthetic drug availability along trade routes. The CCT model offers a scalable, low-cost pharmacological screening framework that can identify individuals at risk before they develop compulsive use patterns. The open-source platforms IMPRINT for addiction-liability screening and TOPOLOGIX for topological data analysis of drug-protein interactions are ready for deployment in resource-limited settings. Endorsements from Kent Berridge at the University of Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at New York University establish the theoretical credibility of this approach. A provisional patent on the CCT core architecture is filed for Q3 2026. The proposed project would pilot a computational screening workshop in partnership with a Djiboutian university or Ministry of Health institution, training local researchers to use IMPRINT and TOPOLOGIX with locally relevant substance use data. This builds local capacity in computational neuroscience and pharmacology while generating Djibouti-specific risk profiles. The Bayesian population dynamics model, published on Zenodo with DOI 10.5281/zenodo.20492472, provides the statistical architecture for translating these screening results into public health recommendations. The U.S. diplomatic mission in Djibouti has a stated interest in countering violent extremism and promoting youth opportunity. Addiction prevention directly supports these goals by reducing vulnerability to recruitment and social destabilization. The CCT model, grounded in mathematical pharmacology and validated through open science, offers a measurable, evidence-based intervention that aligns with U.S. foreign policy objectives in the Horn of Africa. PROJECT NARRATIVE Problem Statement Djibouti's youth population faces increasing exposure to addictive substances, including khat, cannabis, and emerging synthetic drugs. The country lacks computational screening infrastructure for early identification of addiction risk. Existing interventions focus on treatment after dependence develops, which is resource-intensive and has low success rates in low-resource settings. The CCT model addresses this gap by predicting reward-memory encoding vulnerability before compulsive behavior emerges. Proposed Activities Phase One, months one through three: Deploy IMPRINT, the open-source addiction-liability screening platform, on a cohort of 200 Djiboutian youth aged 18 to 25 recruited through a local university or health center. Phase Two, months four through six: Apply TOPOLOGIX, using persistent homology and bipartite simplicial complexes, to analyze drug-protein interaction profiles for substances prevalent in Djibouti, including khat cathinones and any identified synthetic cannabinoids. Phase Three, months seven through nine: Conduct a three-day training workshop for 15 local researchers and health professionals on computational pharmacology methods, including ODE/RK45 simulation, Bayesian MCMC analysis using PyMC, and interpretation of CCT model outputs. Phase Four, months ten through twelve: Produce a Djibouti-specific risk report with Bayesian posterior distributions for encoding probability across demographic subgroups, and deliver policy recommendations to the Ministry of Health and the U.S. Embassy. Expected Outcomes A validated risk screening protocol deployable at primary health centers. A cohort-specific encoding probability distribution with 95 percent credible intervals. Fifteen trained local researchers competent in computational pharmacology. A policy brief connecting CCT model outputs to prevention program design. All code and data deposited on Zenodo with open licenses. Evaluation Plan Pre- and post-training competency assessments for workshop participants. Comparison of IMPRINT screening results against six-month follow-up substance use self-reports. Bayesian model comparison between Djibouti-specific data and the existing validation dataset from Nigerian populations. All analysis scripts published on GitHub under the AmunRaPtah repository. Sustainability IMPRINT and TOPOLOGIX are Apache 2.0 licensed and require only a standard laptop and Python environment to run. The training curriculum will be documented as a reproducible Jupyter notebook pipeline. The Djibouti partner institution will retain all data and code, enabling independent continuation after the grant period. BUDGET NARRATIVE Personnel: 8,000 USD. One month of stipend for the principal investigator, Eniola Ayodele Olutogun, to travel to Djibouti for workshop delivery and data collection oversight. Equipment: 3,000 USD. Two laptops capable of running Python, PyMC, and Gudhi for local researchers who lack adequate computing resources. Travel: 4,000 USD. Round-trip airfare from Lagos to Djibouti City, ground transportation, and per diem for 14 days. Workshop costs: 2,500 USD. Venue rental, printed materials, internet access, and refreshments for 15 participants over three days. Data collection: 1,500 USD. Participant incentives, consent form printing, and mobile data collection subscriptions. Indirect costs: 1,000 USD. Administrative support for grant reporting and financial management. Total requested: 20,000 USD. QUALIFICATIONS STATEMENT Eniola Ayodele Olutogun holds a B.Pharm from the University of Ibadan with a CGPA of 5.1 out of 7.0, German equivalent 1.9, and is a PCN-licensed pharmacist. The CCT model, developed as independent research from 2025 to 2026, is documented in three sole-authored preprints on OSF and Zenodo with DOIs 10.17605/OSF.IO/KG7B5, 10.17605/OSF.IO/EMY4U, and 10.5281/zenodo.20492472. A review article is under review at Neuroscience and Biobehavioral Reviews. A co-authored paper is under review at Alcohol, published by Elsevier. Technical skills include Python with scipy, numpy, PyMC, and pandas; R; topological data analysis with Ripser and Gudhi; neural simulation with NEURON and Brian2; molecular modeling with AlphaFold, RDKit, GROMACS, and AutoDock; and high-performance computing with Nextflow and SLURM. Platforms built include IMPRINT for addiction-liability screening, TOPOLOGIX for topological drug-protein interaction analysis with a hERG cardiotoxicity MVP, and GATE for BCI neural-stimulation safety evaluation, all under Apache 2.0. Endorsements for arXiv submission came from Samuel Gershman at Harvard. Professional experience includes National Product Manager at Synthcare, Clinical Pharmacist at Ramset Pharmacy, research assistant at CDDDP working on NMDA and insulin docking, and bioinformatics researcher at GHRU-GSAR on antimicrobial resistance genomics and surveillance pipelines. A provisional patent on the CCT core architecture is filed for Q3 2026. CHECKLIST - [ ] Complete Grants.gov registration for applicant organization - [ ] Obtain DUNS number or UEI for ZYCO or individual applicant - [ ] Download and complete SF-424 form - [ ] Download and complete SF-424A budget form - [ ] Write and attach project narrative not exceeding 10 pages - [ ] Write and attach budget narrative - [ ] Attach curriculum vitae for Eniola Ayodele Olutogun - [ ] Attach letters of support from Djibouti partner institution - [ ] Attach letter of endorsement from Kent Berridge, Samuel Gershman, Nathaniel Daw, or Marcelo Mattar - [ ] Attach copies of three preprints from OSF and Zenodo - [ ] Attach proof of PCN pharmacist license - [ ] Attach provisional patent filing receipt for CCT core architecture - [ ] Submit through Grants.gov before deadline - [ ] Email confirmation copy to U.S. Embassy Djibouti PDS contact EDITOR NOTES - Verify whether the U.S. Embassy Djibouti PDS programme requires a U.S.-based fiscal sponsor or allows direct application from a Nigerian independent researcher. If a local Djiboutian partner is mandatory, identify and contact a specific institution such as the University of Djibouti or the Ministry of Health research division before submission. - Confirm the exact deadline date on the Grants.gov page, as the prompt states "see programme website" and the deadline may have passed or be imminent. - The budget total of 20,000 USD is an estimate. Confirm whether the programme has a minimum or maximum award amount, and adjust the budget narrative accordingly. If the programme typically funds smaller amounts, scale the activities to a pilot workshop only.