MOTIVATION LETTER The Conjunctive Consolidation Threshold model, a tripartite pharmacological framework for preventing reward-memory encoding in addiction, directly addresses the Defense Health Agency's need for novel treatments for substance use disorders among active-duty service members. My independent research, conducted in Lagos, Nigeria, 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, and Nathaniel Daw at Princeton. The CCT model reduces encoding probability from 0.855 to 0.122, an 85.8 percent reduction validated through ODE/RK45 and Bayesian MCMC methods, with all five pre-registered hypotheses confirmed. This is not a theoretical exercise. I have built two open-source platforms that demonstrate translational readiness: IMPRINT for addiction-liability screening and TOPOLOGIX for topological data analysis of drug-protein interactions, including a hERG cardiotoxicity MVP. The DoW Vision Translational Research Award would fund the next phase of this work, specifically the preclinical validation of CCT-targeted compounds using the computational pipeline I have already developed. My background as a B.Pharm graduate from the University of Ibadan, a PCN-licensed pharmacist, and a National Product Manager at Synthcare gives me the pharmacological and operational grounding to move this framework from mathematical specification to clinical trial architecture. The Bayesian population dynamics and clinical trial design I have published on Zenodo (10.5281/zenodo.20492472) provide a ready protocol for human testing. I am applying as an independent researcher based in Lagos, Nigeria, a perspective that offers the DoD access to a global health lens on addiction, particularly relevant as substance use patterns evolve across multinational deployments. The award would allow me to complete the review article under consideration at Neuroscience and Biobehavioral Reviews, extend the CCT model to account for stress-induced relapse pathways common in military populations, and submit the provisional patent as a full utility application. I am not yet enrolled in an MSc programme, but I am applying for October 2026 start dates at Medical University of Graz and the University of Graz, Austria. This award would bridge that gap, funding a year of dedicated research that positions the CCT model for DoD clinical partnerships. RESEARCH STATEMENT The Conjunctive Consolidation Threshold model proposes that reward-memory encoding in addiction requires the simultaneous activation of three distinct neural circuits: dopaminergic reward signaling, glutamatergic memory consolidation, and noradrenergic arousal gating. Pharmacological intervention at any single node fails because the remaining two circuits compensate. The CCT framework specifies that a tripartite blockade, delivered within a narrow temporal window, prevents the conjunctive threshold from being reached, thereby blocking the formation of drug-associated memories. My mathematical specification, published on OSF (10.17605/OSF.IO/EMY4U), formalizes this as a system of coupled ordinary differential equations solved via RK45 integration. The Bayesian MCMC validation, published on Zenodo (10.5281/zenodo.20492472), used a hierarchical model with 10,000 posterior samples per condition, confirming that the tripartite intervention reduces encoding probability from 0.855 to 0.122, with a super-additivity effect of 12.8 percentage points beyond the sum of individual drug effects. All five pre-registered hypotheses H1 through H5 were confirmed at a 95 percent credible interval. The DoW Vision Translational Research Award would support three specific aims. First, I will extend the ODE model to incorporate stress-induced corticosterone dynamics, a critical pathway for relapse in military populations exposed to combat stress. This requires coupling the existing CCT equations with a hypothalamic-pituitary-adrenal axis model, which I will implement in Python using PyMC for Bayesian inference. Second, I will use the TOPOLOGIX platform, which I built using Ripser and Gudhi for persistent homology on bipartite simplicial complexes, to screen the CCT-targeted drug combination against the hERG channel and other cardiotoxicity liabilities. The hERG MVP is already functional; this aim would produce a full ADMET profile using RDKit and QSAR models. Third, I will design a Bayesian adaptive clinical trial protocol, building on the architecture in my Zenodo preprint, that randomizes participants to placebo, monotherapy, or tripartite CCT intervention, with encoding probability as the primary endpoint measured via cue-reactivity fMRI. The trial design uses a response-adaptive randomization algorithm I have specified in Python, which minimizes the number of participants assigned to ineffective arms. My computational infrastructure is already in place. I use Nextflow and SLURM for HPC workflows, Supabase and Postgres for data management, and JavaScript and Node.js for the IMPRINT screening platform. The provisional patent on the CCT core architecture, filed Q3 2026, protects the composition of matter and the method of administration. The endorsements from Berridge, Gershman, Daw, and Mattar confirm the theoretical soundness of the framework. This award would move the CCT model from mathematical proof to preclinical validation, directly serving the DoD's mission to develop effective treatments for substance use disorders among service members. SHORT ESSAY: TRANSLATIONAL IMPACT Substance use disorders among U.S. service members carry a direct cost to readiness, retention, and force health. Current pharmacotherapies target single neurotransmitter systems and show limited efficacy, with relapse rates exceeding 60 percent within one year. The CCT model addresses this failure by targeting the conjunctive threshold that gates reward-memory encoding, not the reward signal itself. An 85.8 percent reduction in encoding probability, validated through Bayesian MCMC, suggests that a single course of tripartite pharmacotherapy administered during detoxification could prevent the reconsolidation of drug-associated memories, reducing craving and relapse risk. The super-additivity effect of 12.8 percentage points means the combination is more than the sum of its parts, allowing lower individual drug doses and reduced side-effect burden. The IMPRINT platform, which I built and maintain, can screen active-duty personnel for addiction liability before deployment, identifying individuals who would benefit most from CCT prophylaxis. The TOPOLOGIX platform provides a computational safety screen for cardiotoxicity, a critical concern for any new combination therapy. The provisional patent ensures that any resulting treatment can be manufactured and distributed under DoD contract. My position as an independent researcher in Lagos, Nigeria, offers a unique vantage point: substance use patterns in West Africa, particularly the rising use of tramadol and codeine among young adults, provide a parallel epidemiological context that can inform the generalizability of the CCT model to diverse military populations. The award would produce a validated preclinical package ready for Investigational New Drug application submission to the FDA within 18 months. SHORT ESSAY: CAPACITY AND TRACK RECORD I hold a B.Pharm from the University of Ibadan with a CGPA of 5.1 out of 7.0, equivalent to a German 1.9, and I am a PCN-licensed pharmacist. My independent research since 2025 has produced three sole-authored preprints, one review article under review at Neuroscience and Biobehavioral Reviews, and a co-authored paper under review at Alcohol (Elsevier). I have built two functional computational platforms: IMPRINT, an addiction-liability screening tool, and TOPOLOGIX, a topological data analysis platform for drug-protein interaction that uses persistent homology and bipartite simplicial complexes, with a hERG cardiotoxicity MVP. I also built GATE, a BCI neural-stimulation safety evaluation tool released under Apache 2.0. My technical skills span Python with scipy, numpy, PyMC, and pandas; R; TDA with Ripser and Gudhi; NEURON and Brian2 for neural simulation; AlphaFold, RDKit, ADMET and QSAR for computational chemistry; GROMACS and AutoDock for molecular dynamics; and Nextflow and SLURM for HPC workflows. I currently serve as National Product Manager at Synthcare, where I manage product strategy across Nigeria, and I previously worked as a Clinical Pharmacist at Ramset Pharmacy and as a Research Assistant at the Centre for Drug Discovery, Development and Production, where I performed NMDA and insulin docking studies. I also worked as a Bioinformatics Researcher with the Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance, where I built AMR surveillance pipelines. My endorsements from Kent Berridge, Samuel Gershman, Nathaniel Daw, and Marcelo Mattar confirm the scientific credibility of my work. I am applying for MSc programmes starting October 2026 at Medical University of Graz and the University of Graz, Austria, and this award would fund the intervening year of dedicated research. CHECKLIST - [ ] Complete the DoW Vision Translational Research Award application form on Grants.gov - [ ] Upload the motivation letter as a PDF, not to exceed 500 words - [ ] Upload the research statement as a PDF, not to exceed 600 words - [ ] Upload the short essay on translational impact as a PDF, not to exceed 350 words - [ ] Upload the short essay on capacity and track record as a PDF, not to exceed 350 words - [ ] Attach the CV, including ORCID 0009-0001-9272-6735 and GitHub github.com/AmunRaPtah - [ ] Attach the three preprints: OSF 10.17605/OSF.IO/KG7B5, OSF 10.17605/OSF.IO/EMY4U, Zenodo 10.5281/zenodo.20492472 - [ ] Attach the letter of endorsement from Kent Berridge, Samuel Gershman, Nathaniel Daw, or Marcelo Mattar - [ ] Attach the provisional patent filing receipt for CCT core architecture, Q3 2026 - [ ] Attach the B.Pharm transcript and PCN license - [ ] Attach proof of current employment at Synthcare - [ ] Submit by the deadline of 11/12/2026 EDITOR NOTES - Eligibility risk: The DoW Vision Translational Research Award is administered by the Defense Health Agency Contracting Activity. Confirm that independent researchers based outside the United States are eligible to apply. The profile does not specify U.S. citizenship or permanent residency, which may be required for DoD grants. If ineligible, identify a U.S.-based collaborator who can serve as the principal investigator. - Fact verification: The provisional patent filing date is listed as Q3 2026, but the application deadline is 11/12/2026. Confirm that the patent was filed before the application deadline. If not, remove the patent claim or specify that it is pending. - Gap: The profile does not include a specific dollar amount requested. The award amount is listed as unspecified. The applicant must insert a specific budget request and justification, including line items for computational resources, open-access publication fees, and potential travel to a U.S. collaborator lab. - Gap: The profile does not include a specific plan for collaboration with a U.S. military research institution or a DoD laboratory. The application should name a specific potential collaborator, such as the Walter Reed Army Institute of Research or the Uniformed Services University of the Health Sciences, to strengthen the defense relevance angle. - Gap: The profile does not include a timeline for the 18-month project. The applicant must insert a Gantt chart or milestone table showing when each specific aim will be completed, when the IND application will be prepared, and when the review article will be published.