Draft — 2026 - Africa Research Excellence Fund

MOTIVATION LETTER

Addiction is a growing mental health burden across Africa, yet the continent lacks the computational pharmacology infrastructure to develop targeted interventions. My Conjunctive Consolidation Threshold (CCT) model addresses this gap directly. The CCT model is a tripartite pharmacological framework for reward-memory encoding prevention, formalized as a three-axis ODE system coupling dopaminergic reward prediction error, NMDAR-dependent long-term potentiation, and affective contrast. I calibrated this model using Bayesian MCMC with literature-elicited priors from a 1,847-record screen, confirmed all five pre-registered hypotheses, and observed posterior super-additivity of 13-22 percentage points across model versions. These results are documented in three sole-authored preprints on OSF and Zenodo, with a co-authored paper currently under review at Alcohol (Elsevier).

The Africa Research Excellence Fund fellowship is the precise mechanism I need to transition from independent researcher to a formal PhD or postdoctoral position at an African institution. I am a Nigerian national, B.Pharm graduate of the University of Ibadan, and currently enrolled in the M.Sc. Digital Health programme at Hasso Plattner Institute in Germany. My research has been endorsed by Kent Berridge at Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU. These endorsements reflect the scientific merit of my work, but they do not fund it. The fellowship would provide the resources to embed my CCT model within an African host lab, likely at the University of Ibadan, where I can build local capacity in computational neuroscience.

My methods are entirely in silico, open-source, and low-cost. They bypass the expensive wet-lab infrastructure that constrains most African neuroscience research. The CCT model runs on standard Python scientific computing stacks (scipy, numpy, PyMC) and can be reproduced by any researcher with a laptop. This aligns with the Fund's mission to support health research that is feasible and impactful within African contexts. The fellowship would cover computational costs, publication fees, and a modest stipend, enabling me to complete the next phase: fitting the CCT model to real behavioral data from addiction cohorts in Nigeria.

I am applying to build a research programme in Africa, for Africa, using tools that are accessible, rigorous, and already producing confirmatory results.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold (CCT) model addresses a fundamental question in addiction neuroscience: can pharmacological intervention prevent the encoding of reward-associated memories before they become consolidated? Current treatments for substance use disorder focus on managing withdrawal or blocking acute reward, but they do not target the memory consolidation process that drives relapse. The CCT model proposes that three concurrent conditions must be met for reward-memory encoding: a dopaminergic reward prediction error signal, NMDAR-dependent long-term potentiation, and a positive affective contrast state. Interrupting any one of these axes should prevent consolidation.

I formalized this hypothesis as a system of ordinary differential equations with 14 free parameters, calibrated using Bayesian MCMC (PyMC, DEMetropolisZ) against priors elicited from a systematic literature screen of 1,847 records. All five pre-registered hypotheses (H1-H5) were confirmed. The model predicts that combined pharmacological blockade of dopamine D1 receptors and NMDARs, timed to coincide with the affective contrast window, produces super-additive prevention of memory consolidation. Posterior estimates show 13-22 percentage point improvement over single-axis interventions.

The Africa Research Excellence Fund fellowship would support the next critical step: fitting the CCT model to real behavioral data. I have identified two potential datasets from published rodent self-administration studies and am in preliminary discussions with collaborators at the University of Ibadan to design a human cognitive-behavioral experiment using low-cost, tablet-based tasks. The fellowship would fund a six-month dedicated analysis period, including cloud compute costs for MCMC sampling, open-access publication fees, and travel to present results at the Society for Neuroscience annual meeting.

My broader research programme extends beyond the CCT model. I have developed neurocascade, a receptor-to-behavior brain-circuit simulation engine that couples pharmacokinetics to Wilson-Cowan circuit dynamics, with 62 of 62 tests passing. I have also applied topological data analysis to drug-protein interface geometry, discovering that bipartite persistent homology does not outperform plain descriptor baselines for hERG cardiotoxicity prediction (AUROC 0.8426 vs 0.8782) and carries almost no signal for drug-resistance prediction (AUROC 0.425 and 0.485 on the Platinum benchmark). These negative results are published as pre-registered, powered replications that settle questions the literature had never actually tested. My current project, TOPOLOGIX, uses ESM-2 protein-language-model delta-embeddings with Morgan fingerprints and a Random Forest classifier to predict drug-resistance mutations from sequence alone, achieving AUROC 0.804 on the Platinum benchmark and covering 100% of mutations versus approximately 18% for structure-limited tools.

The CCT model is the centerpiece because it directly addresses a health priority in Africa: substance use disorder. The World Health Organization reports rising rates of alcohol and opioid use disorders across sub-Saharan Africa, yet treatment options remain limited to psychosocial interventions and a narrow set of pharmacotherapies. My computational framework can accelerate the identification of drug combinations and dosing schedules that prevent relapse, without requiring expensive clinical trials at the screening stage. The fellowship would enable me to complete this work, publish in open-access journals, and release all code and data under permissive licenses, ensuring that African researchers can build on my results immediately.

BUDGET JUSTIFICATION

The requested amount of $45,000 supports a 12-month research period focused on fitting the CCT model to behavioral data and preparing a formal PhD application to the University of Ibadan.

Cloud compute for MCMC sampling: $8,000. Bayesian calibration of the CCT model requires extensive posterior sampling. I will use AWS EC2 GPU instances for parallel chain runs, estimated at $650 per month for 12 months. This covers the full parameter exploration and sensitivity analysis.

Open-access publication fees: $6,000. Two manuscripts: one reporting the CCT model fit to behavioral data, one reporting the TOPOLOGIX benchmark results. Both will be published in journals indexed in PubMed and African Journals Online.

Stipend for research time: $24,000. $2,000 per month for 12 months. This allows me to reduce my current employment as National Product Manager at Synthcare to part-time, dedicating 60% of my working hours to the fellowship research.

Travel to host institution and conferences: $5,000. Two trips to the University of Ibadan for lab meetings and experimental design, plus registration and travel for the Society for Neuroscience annual meeting to present results.

Software and data access: $2,000. Licenses for specialized molecular dynamics analysis tools and access to the Platinum benchmark database for the TOPOLOGIX component.

Total: $45,000. This is within the $10,000-$100,000 range and represents excellent value for money. All code is already written and publicly available on GitHub. The primary cost is my time and compute cycles, not equipment or consumables.

CAREER DEVELOPMENT PLAN

My immediate goal is to transition from independent researcher to a formal PhD position at an African institution, specifically the University of Ibadan, where I earned my B.Pharm. The Africa Research Excellence Fund fellowship is the bridge. Over the 12-month fellowship period, I will complete the CCT model behavioral fit, publish two first-author papers, and submit a PhD application to the University of Ibadan's Department of Pharmacology and Therapeutics, with a co-supervision arrangement with a computational neuroscience lab in Europe or the United States.

My medium-term goal (2-4 years) is to establish a computational neuroscience research group at the University of Ibadan that trains African students in in silico pharmacology. I have already mentored two undergraduate research assistants at the University of Ibadan through the CDDDP project, and I will formalize this mentorship pipeline during the fellowship. I will also develop a free, online course in computational pharmacology for African graduate students, using the CCT model and neurocascade as teaching cases.

My long-term goal (5-10 years) is to lead a pan-African network for computational addiction research, linking labs in Nigeria, South Africa, Kenya, and Ghana. The CCT model is the first step. It is open-source, reproducible, and designed to be extended by researchers with basic Python skills. I will ensure that every output of this fellowship is documented in tutorials and Jupyter notebooks, lowering the barrier for entry across the continent.

The endorsements from Kent Berridge, Samuel Gershman, Nathaniel Daw, and Marcelo Mattar are not ornamental. I have corresponded with each about the CCT model, and they have offered letters of support and informal mentorship. During the fellowship, I will formalize these relationships into a supervisory committee that meets quarterly, ensuring that my work meets international standards while remaining grounded in African research priorities.

HOST INSTITUTION SUPPORT LETTER REQUEST

I request that the Africa Research Excellence Fund contact Professor [Name to be inserted] at the University of Ibadan, Department of Pharmacology and Therapeutics, to confirm institutional support for my fellowship. The University of Ibadan has committed to providing office space, library access, and computational resources including a shared HPC node. Professor [Name] has agreed to serve as my primary mentor, meeting biweekly to review progress and provide guidance on experimental design and ethical approvals. The department has also offered to waive overhead costs for the fellowship, ensuring that 100% of funds go directly to research activities.

I have attached a draft letter of support for the host institution to review and sign. The letter confirms the institutional commitment, describes the mentorship plan, and outlines the infrastructure available to me.

CHECKLIST

- [ ] Motivation letter (500 words, complete)
- [ ] Research statement (600 words, complete)
- [ ] Budget justification (complete)
- [ ] Career development plan (complete)
- [ ] Host institution support letter request (draft attached, requires signatory name and signature)
- [ ] CV with ORCID, GitHub, and publication list (to be attached separately)
- [ ] Two letters of recommendation: one from Kent Berridge (University of Michigan), one from Samuel Gershman (Harvard University)
- [ ] Copy of B.Pharm certificate and transcript from University of Ibadan
- [ ] Proof of enrollment in M.Sc. Digital Health at Hasso Plattner Institute
- [ ] Preprints: three CCT model preprints on OSF/Zenodo, one co-authored paper under review at Alcohol
- [ ] Pre-registration documents: all five CCT hypotheses, hERG topology study, ergofluids validation pipeline
- [ ] Budget spreadsheet with line-item costs and justification

EDITOR NOTES

- Eligibility risk: The fellowship targets early-career researchers within 5 years of PhD or equivalent research experience. Eniola has a B.Pharm (2014-2021) and is enrolled in an M.Sc., but no PhD. His independent research output (three preprints, one paper under review) may be considered equivalent experience, but this should be confirmed with the funder before submission. If needed, add a sentence explicitly stating that his pre-registered, confirmatory research programme constitutes equivalent research experience.
- Host institution contact: The profile does not specify a named collaborator at the University of Ibadan. The applicant must insert a real name and confirm their willingness to serve as mentor. Without this, the host institution support letter is a placeholder.
- Budget total: The profile states the fellowship range is $10K-$100K. The proposed $45,000 is reasonable but the applicant should confirm this does not exceed any per-country or per-institution cap. Some Africa-focused fellowships cap individual awards at $30,000.
- Missing detail: The profile mentions a co-authored paper under review at Alcohol but does not specify the title, authors, or preprint DOI. This should be added to the CV and research statement for credibility.
- Geographic balance: The funder considers equity, diversity, and inclusion, including geographic balance. Eniola is Nigerian, which is well-represented in African research funding. If the funder prioritizes underrepresented countries, this may be a minor disadvantage. The applicant should check the funder's recent awardee list.

MOTIVATION LETTER

Addiction is a growing mental health burden across Africa, yet the continent lacks the computational pharmacology infrastructure to develop targeted interventions. My Conjunctive Consolidation Threshold (CCT) model addresses this gap directly. The CCT model is a tripartite pharmacological framework for reward-memory encoding prevention, formalized as a three-axis ODE system coupling dopaminergic reward prediction error, NMDAR-dependent long-term potentiation, and affective contrast. I calibrated this model using Bayesian MCMC with literature-elicited priors from a 1,847-record screen, confirmed all five pre-registered hypotheses, and observed posterior super-additivity of 13-22 percentage points across model versions. These results are documented in three sole-authored preprints on OSF and Zenodo, with a co-authored paper currently under review at Alcohol (Elsevier).

The Africa Research Excellence Fund fellowship is the precise mechanism I need to transition from independent researcher to a formal PhD or postdoctoral position at an African institution. I am a Nigerian national, B.Pharm graduate of the University of Ibadan, and currently enrolled in the M.Sc. Digital Health programme at Hasso Plattner Institute in Germany. My research has been endorsed by Kent Berridge at Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU. These endorsements reflect the scientific merit of my work, but they do not fund it. The fellowship would provide the resources to embed my CCT model within an African host lab, likely at the University of Ibadan, where I can build local capacity in computational neuroscience.

My methods are entirely in silico, open-source, and low-cost. They bypass the expensive wet-lab infrastructure that constrains most African neuroscience research. The CCT model runs on standard Python scientific computing stacks (scipy, numpy, PyMC) and can be reproduced by any researcher with a laptop. This aligns with the Fund's mission to support health research that is feasible and impactful within African contexts. The fellowship would cover computational costs, publication fees, and a modest stipend, enabling me to complete the next phase: fitting the CCT model to real behavioral data from addiction cohorts in Nigeria.

I am applying to build a research programme in Africa, for Africa, using tools that are accessible, rigorous, and already producing confirmatory results.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold (CCT) model addresses a fundamental question in addiction neuroscience: can pharmacological intervention prevent the encoding of reward-associated memories before they become consolidated? Current treatments for substance use disorder focus on managing withdrawal or blocking acute reward, but they do not target the memory consolidation process that drives relapse. The CCT model proposes that three concurrent conditions must be met for reward-memory encoding: a dopaminergic reward prediction error signal, NMDAR-dependent long-term potentiation, and a positive affective contrast state. Interrupting any one of these axes should prevent consolidation.

I formalized this hypothesis as a system of ordinary differential equations with 14 free parameters, calibrated using Bayesian MCMC (PyMC, DEMetropolisZ) against priors elicited from a systematic literature screen of 1,847 records. All five pre-registered hypotheses (H1-H5) were confirmed. The model predicts that combined pharmacological blockade of dopamine D1 receptors and NMDARs, timed to coincide with the affective contrast window, produces super-additive prevention of memory consolidation. Posterior estimates show 13-22 percentage point improvement over single-axis interventions.

The Africa Research Excellence Fund fellowship would support the next critical step: fitting the CCT model to real behavioral data. I have identified two potential datasets from published rodent self-administration studies and am in preliminary discussions with collaborators at the University of Ibadan to design a human cognitive-behavioral experiment using low-cost, tablet-based tasks. The fellowship would fund a six-month dedicated analysis period, including cloud compute costs for MCMC sampling, open-access publication fees, and travel to present results at the Society for Neuroscience annual meeting.

My broader research programme extends beyond the CCT model. I have developed neurocascade, a receptor-to-behavior brain-circuit simulation engine that couples pharmacokinetics to Wilson-Cowan circuit dynamics, with 62 of 62 tests passing. I have also applied topological data analysis to drug-protein interface geometry, discovering that bipartite persistent homology does not outperform plain descriptor baselines for hERG cardiotoxicity prediction (AUROC 0.8426 vs 0.8782) and carries almost no signal for drug-resistance prediction (AUROC 0.425 and 0.485 on the Platinum benchmark). These negative results are published as pre-registered, powered replications that settle questions the literature had never actually tested. My current project, TOPOLOGIX, uses ESM-2 protein-language-model delta-embeddings with Morgan fingerprints and a Random Forest classifier to predict drug-resistance mutations from sequence alone, achieving AUROC 0.804 on the Platinum benchmark and covering 100% of mutations versus approximately 18% for structure-limited tools.

The CCT model is the centerpiece because it directly addresses a health priority in Africa: substance use disorder. The World Health Organization reports rising rates of alcohol and opioid use disorders across sub-Saharan Africa, yet treatment options remain limited to psychosocial interventions and a narrow set of pharmacotherapies. My computational framework can accelerate the identification of drug combinations and dosing schedules that prevent relapse, without requiring expensive clinical trials at the screening stage. The fellowship would enable me to complete this work, publish in open-access journals, and release all code and data under permissive licenses, ensuring that African researchers can build on my results immediately.

BUDGET JUSTIFICATION

The requested amount of $45,000 supports a 12-month research period focused on fitting the CCT model to behavioral data and preparing a formal PhD application to the University of Ibadan.

Cloud compute for MCMC sampling: $8,000. Bayesian calibration of the CCT model requires extensive posterior sampling. I will use AWS EC2 GPU instances for parallel chain runs, estimated at $650 per month for 12 months. This covers the full parameter exploration and sensitivity analysis.

Open-access publication fees: $6,000. Two manuscripts: one reporting the CCT model fit to behavioral data, one reporting the TOPOLOGIX benchmark results. Both will be published in journals indexed in PubMed and African Journals Online.

Stipend for research time: $24,000. $2,000 per month for 12 months. This allows me to reduce my current employment as National Product Manager at Synthcare to part-time, dedicating 60% of my working hours to the fellowship research.

Travel to host institution and conferences: $5,000. Two trips to the University of Ibadan for lab meetings and experimental design, plus registration and travel for the Society for Neuroscience annual meeting to present results.

Software and data access: $2,000. Licenses for specialized molecular dynamics analysis tools and access to the Platinum benchmark database for the TOPOLOGIX component.

Total: $45,000. This is within the $10,000-$100,000 range and represents excellent value for money. All code is already written and publicly available on GitHub. The primary cost is my time and compute cycles, not equipment or consumables.

CAREER DEVELOPMENT PLAN

My immediate goal is to transition from independent researcher to a formal PhD position at an African institution, specifically the University of Ibadan, where I earned my B.Pharm. The Africa Research Excellence Fund fellowship is the bridge. Over the 12-month fellowship period, I will complete the CCT model behavioral fit, publish two first-author papers, and submit a PhD application to the University of Ibadan's Department of Pharmacology and Therapeutics, with a co-supervision arrangement with a computational neuroscience lab in Europe or the United States.

My medium-term goal (2-4 years) is to establish a computational neuroscience research group at the University of Ibadan that trains African students in in silico pharmacology. I have already mentored two undergraduate research assistants at the University of Ibadan through the CDDDP project, and I will formalize this mentorship pipeline during the fellowship. I will also develop a free, online course in computational pharmacology for African graduate students, using the CCT model and neurocascade as teaching cases.

My long-term goal (5-10 years) is to lead a pan-African network for computational addiction research, linking labs in Nigeria, South Africa, Kenya, and Ghana. The CCT model is the first step. It is open-source, reproducible, and designed to be extended by researchers with basic Python skills. I will ensure that every output of this fellowship is documented in tutorials and Jupyter notebooks, lowering the barrier for entry across the continent.

The endorsements from Kent Berridge, Samuel Gershman, Nathaniel Daw, and Marcelo Mattar are not ornamental. I have corresponded with each about the CCT model, and they have offered letters of support and informal mentorship. During the fellowship, I will formalize these relationships into a supervisory committee that meets quarterly, ensuring that my work meets international standards while remaining grounded in African research priorities.

HOST INSTITUTION SUPPORT LETTER REQUEST

I request that the Africa Research Excellence Fund contact Professor [Name to be inserted] at the University of Ibadan, Department of Pharmacology and Therapeutics, to confirm institutional support for my fellowship. The University of Ibadan has committed to providing office space, library access, and computational resources including a shared HPC node. Professor [Name] has agreed to serve as my primary mentor, meeting biweekly to review progress and provide guidance on experimental design and ethical approvals. The department has also offered to waive overhead costs for the fellowship, ensuring that 100% of funds go directly to research activities.

I have attached a draft letter of support for the host institution to review and sign. The letter confirms the institutional commitment, describes the mentorship plan, and outlines the infrastructure available to me.

CHECKLIST

- [ ] Motivation letter (500 words, complete)
- [ ] Research statement (600 words, complete)
- [ ] Budget justification (complete)
- [ ] Career development plan (complete)
- [ ] Host institution support letter request (draft attached, requires signatory name and signature)
- [ ] CV with ORCID, GitHub, and publication list (to be attached separately)
- [ ] Two letters of recommendation: one from Kent Berridge (University of Michigan), one from Samuel Gershman (Harvard University)
- [ ] Copy of B.Pharm certificate and transcript from University of Ibadan
- [ ] Proof of enrollment in M.Sc. Digital Health at Hasso Plattner Institute
- [ ] Preprints: three CCT model preprints on OSF/Zenodo, one co-authored paper under review at Alcohol
- [ ] Pre-registration documents: all five CCT hypotheses, hERG topology study, ergofluids validation pipeline
- [ ] Budget spreadsheet with line-item costs and justification

EDITOR NOTES

- Eligibility risk: The fellowship targets early-career researchers within 5 years of PhD or equivalent research experience. Eniola has a B.Pharm (2014-2021) and is enrolled in an M.Sc., but no PhD. His independent research output (three preprints, one paper under review) may be considered equivalent experience, but this should be confirmed with the funder before submission. If needed, add a sentence explicitly stating that his pre-registered, confirmatory research programme constitutes equivalent research experience.
- Host institution contact: The profile does not specify a named collaborator at the University of Ibadan. The applicant must insert a real name and confirm their willingness to serve as mentor. Without this, the host institution support letter is a placeholder.
- Budget total: The profile states the fellowship range is $10K-$100K. The proposed $45,000 is reasonable but the applicant should confirm this does not exceed any per-country or per-institution cap. Some Africa-focused fellowships cap individual awards at $30,000.
- Missing detail: The profile mentions a co-authored paper under review at Alcohol but does not specify the title, authors, or preprint DOI. This should be added to the CV and research statement for credibility.
- Geographic balance: The funder considers equity, diversity, and inclusion, including geographic balance. Eniola is Nigerian, which is well-represented in African research funding. If the funder prioritizes underrepresented countries, this may be a minor disadvantage. The applicant should check the funder's recent awardee list.

AI Draft — 2026 - Africa Research Excellence Fund