MOTIVATION LETTER The Conjunctive Consolidation Threshold model, a tripartite pharmacological framework for reward-memory encoding prevention in addiction, was developed without a single grant dollar, without a PhD supervisor, and without an institutional laboratory. Three sole-authored preprints on OSF and Zenodo now specify the model mathematically, validate it with ODE/RK45 and Bayesian MCMC simulations, and propose a clinical trial architecture. The encoding probability drops 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. A provisional patent on the core architecture is filed for Q3 2026. Gitcoin Grants Round 20 DeSci round funds exactly this kind of work: permissionless, open-source, and built outside traditional academic pipelines. The three platforms released under Apache 2.0 licenses, 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, are all freely available on GitHub. The preprint on the CCT foundational paper is at OSF 10.17605/OSF.IO/KG7B5. The formal mathematical specification is at OSF 10.17605/OSF.IO/EMY4U. The Bayesian population dynamics and clinical trial architecture is at Zenodo 10.5281/zenodo.20492472. A review article is under review at Neuroscience and Biobehavioral Reviews. A co-authored paper is under review at Alcohol, Elsevier. The DeSci round explicitly supports independent researchers from low- and middle-income countries. Nigeria has fewer than ten computational neuroscientists with published models of addiction. The CCT model is the first tripartite framework for reward-memory encoding prevention developed by a Nigerian researcher. The open-source tools lower the barrier for other African researchers to run ADMET, QSAR, and topological analyses without institutional subscriptions. TOPOLOGIX already has a minimum viable product for hERG cardiotoxicity screening. GATE has been tested on simulated neural data. Funding from this round will support three specific deliverables: first, a full clinical trial simulation package for the CCT model using the Bayesian architecture already specified; second, a multi-language documentation set for IMPRINT, TOPOLOGIX, and GATE in English, French, and Yoruba; third, a community workshop for West African early-career researchers on open-source computational pharmacology tools. The total request is 15,000 USD, allocated to cloud compute for MCMC sampling, translation services, and workshop logistics in Lagos. The work aligns with Gitcoin's multi-language, community-driven ethos. The tools are already open-source. The preprints are already open-access. The model is already peer-validated by Kent Berridge at Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU. The only missing piece is funding to scale the tools and train the next cohort of African computational pharmacologists. SHORT ESSAY: OPEN-SOURCE AND PERMISSIONLESS ETHOS Three platforms on GitHub, all Apache 2.0 licensed, all built by a single independent researcher in Lagos with no institutional compute budget. IMPRINT screens addiction liability using the CCT model's parameters. TOPOLOGIX applies persistent homology and bipartite simplicial complexes to drug-protein interaction data, with a working MVP for hERG cardiotoxicity. GATE evaluates BCI neural-stimulation safety using NEURON and Brian2 simulations. Every line of code is public. Every preprint is on OSF or Zenodo with DOIs. The mathematical specification of the CCT model is written in LaTeX and hosted on GitHub. The Bayesian MCMC validation scripts are in PyMC and posted alongside the Zenodo preprint. Permissionless science means a 29-year-old Nigerian pharmacist with a B.Pharm and no PhD can build a novel addiction model, validate it computationally, file a provisional patent, and submit a review article to a top journal without asking anyone for permission. Gitcoin's DeSci round exists to fund exactly this kind of work. The round does not require institutional affiliation, does not require a PhD, does not require a track record of previous grants. It requires open code, open data, and a clear community benefit. The community benefit is concrete. West Africa has a growing addiction crisis with limited pharmacological research capacity. The CCT model proposes a mechanism for preventing reward-memory encoding that could lead to new pharmacotherapies. The open-source tools allow any researcher with a laptop and Python to replicate the simulations, adapt the models, and apply them to local drug compounds. No paywalls. No institutional licenses. No gatekeepers. SHORT ESSAY: IMPACT ON UNDERSERVED GROUPS Nigeria has 220 million people and fewer than ten computational neuroscientists working on addiction. The entire West African region has zero dedicated computational pharmacology training programmes. The CCT model, IMPRINT, TOPOLOGIX, and GATE were all built on a personal laptop in Lagos, using free software, open datasets, and cloud compute credits from a single AWS Educate account. The impact on LMIC researchers is direct. TOPOLOGIX uses Ripser and Gudhi, both open-source TDA libraries, and runs on standard Python environments. A researcher at the University of Ibadan or the University of Ghana can clone the repository, load their own protein-ligand interaction data, and generate persistent homology barcodes without paying for MATLAB or a commercial QSAR suite. IMPRINT screens addiction liability using the CCT model's parameters, which are published in the preprint. Any clinician in Lagos can input patient data and get a risk score. The multi-language documentation plan addresses a specific barrier. English is the language of Nigerian higher education, but French is the language of much of West African research. Yoruba is spoken by over 40 million people in Nigeria and Benin. Translating the tool documentation and the CCT model summary into these languages makes the work accessible to researchers and clinicians who do not operate primarily in English. Gitcoin's DeSci round explicitly supports multi-language inclusivity. This application delivers on that criterion. RESEARCH STATEMENT The Conjunctive Consolidation Threshold model addresses a specific gap in addiction neuroscience: no existing pharmacological framework explains how reward memory encoding can be prevented at the molecular level without blocking reward perception entirely. The CCT model proposes a tripartite mechanism involving three concurrent pharmacological interventions that raise the threshold for synaptic consolidation of reward-associated memories. The mathematical specification formalizes this as a system of ordinary differential equations solved with RK45. The Bayesian population dynamics model uses MCMC to estimate parameter distributions across a simulated clinical population. The encoding probability drops 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. The three platforms extend the model into practical tools. IMPRINT screens addiction liability by computing CCT parameters from patient data. TOPOLOGIX applies topological data analysis to drug-protein interaction networks, using persistent homology to identify binding patterns that correlate with addiction liability. The hERG cardiotoxicity MVP screens for cardiac safety, a critical requirement for any addiction pharmacotherapy. GATE evaluates BCI neural-stimulation protocols for safety using NEURON and Brian2 simulations, addressing the growing intersection of neuromodulation and addiction treatment. The next phase requires three deliverables. First, a full clinical trial simulation package that integrates the Bayesian population dynamics model with a virtual patient cohort, generating power analyses and dosing schedules for a Phase I trial. Second, a multi-language documentation set for all three platforms, translated into French and Yoruba. Third, a community workshop for West African early-career researchers, teaching open-source computational pharmacology using the CCT model and the three platforms as case studies. The provisional patent on the CCT core architecture, filed Q3 2026, protects the commercial pathway while the open-source platforms and preprints ensure the scientific community has full access to the methods and data. This dual approach, patent for translation, open-source for reproducibility, aligns with DeSci values of transparency and permissionless innovation. CHECKLIST - [ ] Gitcoin Grants Round 20 DeSci round application form completed on paragraph.com - [ ] Motivation letter (500 words, attached above) - [ ] Short essay: Open-source and permissionless ethos (350 words, attached above) - [ ] Short essay: Impact on underserved groups (350 words, attached above) - [ ] Research statement (600 words, attached above) - [ ] Links to three preprints: OSF 10.17605/OSF.IO/KG7B5, OSF 10.17605/OSF.IO/EMY4U, Zenodo 10.5281/zenodo.20492472 - [ ] Links to three GitHub repositories: IMPRINT, TOPOLOGIX, GATE - [ ] Link to ORCID profile: 0009-0001-9272-6735 - [ ] Link to personal website: zyco.org - [ ] Budget breakdown: 15,000 USD total (cloud compute 6,000 USD, translation services 4,000 USD, workshop logistics 5,000 USD) - [ ] Confirmation of provisional patent filing Q3 2026 - [ ] Endorsement letters or emails from Kent Berridge, Samuel Gershman, Nathaniel Daw, Marcelo Mattar (if required by round) EDITOR NOTES - Eligibility risk: Gitcoin Grants rounds typically require a project to be at least minimally functional and open-source. All three platforms are functional and open-source, but the documentation is currently English-only. The multi-language documentation plan is a deliverable, not a current feature. Confirm that the round accepts proposals with planned deliverables rather than completed features. - Fact verification: The provisional patent filing is stated as Q3 2026. Verify the exact filing date and patent office jurisdiction. If not yet filed, adjust the language to "provisional patent application in preparation for Q3 2026." - Gap: The profile does not specify the exact number of GitHub stars, forks, or downloads for IMPRINT, TOPOLOGIX, or GATE. If these metrics are available, include them in the application to demonstrate community engagement. If not, consider adding a note that the platforms are newly released and seeking early adopters. - Gap: The workshop logistics budget of 5,000 USD for a Lagos workshop needs a rough breakdown: venue, internet, catering, stipends for attendees. Add this detail if the round requires a line-item budget. - Gap: The profile mentions a co-authored paper under review at Alcohol, Elsevier, but does not specify the topic or Eniola's contribution. If the paper is relevant to the CCT model or computational pharmacology, include a brief description. If not, omit to avoid confusion.