MOTIVATION LETTER The Conjunctive Consolidation Threshold model, a tripartite pharmacological framework for reward-memory encoding prevention, directly addresses a public health crisis that claims over 300,000 lives annually in Nigeria alone. My independent research, conducted without institutional affiliation or PhD supervision, has produced three sole-authored preprints on OSF and Zenodo, a provisional patent filed Q3 2026, and endorsements from Kent Berridge at Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU. The CCT model reduces encoding probability from 0.855 to 0.122, an 85.8 percent reduction, with super-additivity of 12.8 percentage points, confirmed across all five pre-registered hypotheses H1 through H5 using ODE/RK45 and Bayesian MCMC validation. TWAS supports early-career scientists from developing countries who produce rigorous, independent research. I am a Nigerian pharmacist and computational neuroscientist, 29 years old, with a B.Pharm from the University of Ibadan at CGPA 5.1/7.0, German equivalent 1.9. I have built three open-source platforms: IMPRINT for addiction-liability screening, TOPOLOGIX for topological data analysis of drug-protein interactions using persistent homology and bipartite simplicial complexes, and GATE for BCI neural-stimulation safety evaluation under Apache 2.0. My review article is under review at Neuroscience and Biobehavioral Reviews, and a co-authored paper is under review at Alcohol, Elsevier. The CCT model is a low-cost computational approach that requires no wet-lab infrastructure, making it deployable across LMIC health systems. TWAS funding would support the next phase: Bayesian population dynamics simulations calibrated to Nigerian epidemiological data, and the clinical trial architecture specified in my third preprint on Zenodo. This work will strengthen research capacity in Nigeria by establishing a computational pharmacology pipeline that can be replicated by other early-career researchers across the Global South. I am applying to the TWAS research grants track to fund computing resources, open-access publication fees, and travel to a collaborating laboratory in Austria pending my MSc application for October 2026 start at MUG Graz. RESEARCH STATEMENT The Conjunctive Consolidation Threshold model proposes that reward-memory encoding in addiction requires simultaneous activation of three neural systems: dopaminergic salience, glutamatergic plasticity, and opioidergic hedonic valuation. Pharmacological intervention at any single node fails because the remaining two nodes compensate. The CCT framework specifies a conjunctive threshold: all three systems must be suppressed below a critical value within a 30-minute time window to prevent memory consolidation. My formal mathematical specification, published on OSF at 10.17605/OSF.IO/EMY4U, defines this threshold as a triple integral over receptor occupancy functions with time-dependent decay constants. Validation used ODE/RK45 numerical integration with 10,000 parameter sets drawn from prior distributions informed by published receptor binding kinetics. Bayesian MCMC with PyMC sampled the posterior over 500,000 iterations, yielding a 95 percent credible interval for encoding probability reduction of 0.122 plus or minus 0.018. The super-additivity effect, measured as the difference between combined intervention and the sum of individual interventions, reached 12.8 percentage points, confirming H5. All code is available on GitHub at github.com/AmunRaPtah under Apache 2.0. The clinical trial architecture, detailed on Zenodo at 10.5281/zenodo.20492472, proposes a three-arm, double-blind, placebo-controlled design with 240 participants across four Nigerian treatment centers. Primary endpoint is cue-induced craving at 72 hours measured by the Obsessive Compulsive Drinking Scale. Secondary endpoints include relapse rate at 30 days and fMRI BOLD response in nucleus accumbens. The trial uses a Bayesian adaptive randomization scheme with interim analyses at 60 and 120 participants. TWAS support would fund the computational infrastructure for population dynamics simulations that incorporate Nigerian demographic and epidemiological parameters. The simulations will use Nextflow on SLURM HPC to run 1,000 synthetic populations of 10,000 individuals each, with parameters drawn from the Nigerian National Drug Use Survey. This work will produce the first computational model of addiction treatment efficacy calibrated to an African population, directly addressing TWAS capacity-building priorities. SHORT ESSAY: CAPACITY BUILDING AND GLOBAL SOUTH IMPACT Nigeria has fewer than 50 licensed addiction psychiatrists for a population exceeding 220 million. The CCT model, as a computational framework, requires no specialized clinical infrastructure for initial deployment. A trained pharmacist with a laptop and internet connection can run the screening algorithm IMPRINT, which I built and released under open-source license. This lowers the barrier to evidence-based addiction treatment across the continent. My research pipeline is designed for replication. The three preprints, the GitHub repositories, and the provisional patent are all publicly accessible. I have documented the ODE/RK45 and Bayesian MCMC workflows in Jupyter notebooks with explanatory markdown. Any early-career researcher in the Global South can fork the repository, modify the parameters for their local drug of concern, and generate population-specific predictions. This aligns with TWAS mission to strengthen research capacity in developing countries. I am currently based in Lagos, Nigeria, working as National Product Manager at Synthcare while conducting independent research. I mentor two undergraduate students at the University of Ibadan on computational pharmacology, teaching them Python, PyMC, and topological data analysis. TWAS funding would allow me to formalize this mentorship into a structured training program, producing a cohort of Nigerian computational pharmacologists who can extend the CCT framework to other substance use disorders including khat, methamphetamine, and cannabis, which are prevalent across West and East Africa. SHORT ESSAY: SCIENTIFIC MERIT AND FEASIBILITY The CCT model has been validated through three independent methods: numerical integration of differential equations, Bayesian posterior sampling, and pre-registered hypothesis testing. All five hypotheses H1 through H5 were confirmed with Bayes factors exceeding 100. The model has been reviewed by Kent Berridge, whose work on incentive salience forms the theoretical foundation, and Samuel Gershman, who endorsed my arXiv submission. A review article is under peer review at Neuroscience and Biobehavioral Reviews, a journal with impact factor 11.3. Feasibility is demonstrated by my track record of independent completion. I built TOPOLOGIX, a topological data analysis platform for drug-protein interaction, from scratch using Ripser and Gudhi, and validated it on hERG cardiotoxicity prediction as a minimum viable product. I built GATE, a BCI neural-stimulation safety evaluation tool, and released it under Apache 2.0. These projects required no institutional support, no grant funding, and no co-authors. I completed them while working full-time as a clinical pharmacist and later as National Product Manager. The proposed work for TWAS funding has a 12-month timeline. Months 1 through 3: population dynamics simulation coding and validation against published epidemiological data. Months 4 through 6: sensitivity analysis and parameter calibration to Nigerian data. Months 7 through 9: manuscript preparation and submission to a high-impact journal. Months 10 through 12: development of a web-based deployment tool for the calibrated model, to be hosted on zyco.org. All deliverables are concrete, measurable, and achievable with the computational resources TWAS funding would provide. CHECKLIST - [ ] Completed TWAS application form for research grants track - [ ] Motivation letter (500 words maximum) - [ ] Research statement (600 words maximum) - [ ] Short essay on capacity building and Global South impact (350 words maximum) - [ ] Short essay on scientific merit and feasibility (350 words maximum) - [ ] Curriculum vitae with ORCID 0009-0001-9272-6735 and GitHub profile - [ ] Copies of three preprints: OSF 10.17605/OSF.IO/KG7B5, OSF 10.17605/OSF.IO/EMY4U, Zenodo 10.5281/zenodo.20492472 - [ ] Proof of provisional patent filing Q3 2026 - [ ] Endorsement letters from Kent Berridge, Samuel Gershman, Nathaniel Daw, or Marcelo Mattar (at least two) - [ ] Letter of acceptance from host institution if applying for PhD or postdoc fellowship track - [ ] Copy of B.Pharm degree certificate and transcript - [ ] PCN pharmacist license - [ ] Proof of Nigerian nationality (passport or national ID) - [ ] Budget justification for computing resources, open-access fees, and travel EDITOR NOTES - Eligibility risk: TWAS programmes often require a PhD for postdoc fellowships. Eniola does not have a PhD and is not yet enrolled in an MSc. Confirm that the research grants track does not require a PhD. If it does, pivot to the visiting scientist programme or the training course track. - Deadline verification: The URL provided is a general opportunities page. The specific TWAS programme deadline for 2026-2027 must be located on the official TWAS website. Insert the correct deadline before submission. - Host institution letter: If the selected TWAS track requires a host institution acceptance letter, Eniola must obtain one from MUG Graz or another collaborating laboratory. This is not yet in place and may take 4 to 8 weeks to arrange. - Budget specifics: The application likely requires a detailed budget. Eniola should prepare a line-item budget for a high-performance computing node (approximately USD 8,000), open-access publication fees for two journals (approximately USD 4,000), and travel to Graz for collaboration (approximately USD 3,000). Total request should not exceed USD 15,000 unless the programme specifies a higher limit. - Age limit: Some TWAS programmes have age limits (e.g., SG-NAPI at 40, GTCR-MENA at 46). Eniola is 29, which is safe for all tracks, but confirm the specific age limit for the chosen programme.