Draft — NSF Trailblazer Engineering Impact Award (TRAILBLAZER)

MOTIVATION LETTER

The NSF Trailblazer Engineering Impact Award supports individual investigators who propose novel research projects with the potential to address new areas of fundamental research and catalyze development of new capabilities. My project, the Conjunctive Consolidation Threshold (CCT) model, is a tripartite pharmacological framework for reward-memory encoding prevention in addiction. I am an independent researcher based in Lagos, Nigeria, with a B.Pharm from the University of Ibadan, three sole-authored preprints on OSF and Zenodo, and endorsements from Kent Berridge at the University of Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU. The CCT model has been validated through ODE/RK45 and Bayesian MCMC methods, demonstrating an encoding probability reduction 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 CCT core architecture is scheduled for Q3 2026.

This project directly addresses the U.S. opioid crisis, a national need that the NSF Trailblazer program is designed to confront through bold, high-risk engineering approaches. The CCT model proposes a new class of pharmacological interventions that prevent the encoding of reward-memory associations, a mechanism distinct from existing addiction treatments that target dopamine signaling or opioid receptors. My background in computational neuroscience, Bayesian modeling, and pharmacology positions me to execute this work. I have built three 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. My technical skills include Python with scipy, numpy, PyMC, and MCMC methods, as well as NEURON, Brian2, AlphaFold, RDKit, ADMET/QSAR, GROMACS, and AutoDock.

I seek to partner with a U.S. academic host institution where one of my collaborators can serve as co-PI. Kent Berridge at the University of Michigan, Nathaniel Daw at Princeton, or Marcelo Mattar at NYU have each reviewed my preprints and endorsed the CCT framework. This partnership will provide the institutional infrastructure, laboratory resources, and student mentorship required for a five-year research program. My independent track record, including a review article under review at Neuroscience and Biobehavioral Reviews and a co-authored paper under review at Alcohol (Elsevier), demonstrates my capacity to lead a novel research direction without prior doctoral training. The NSF Trailblazer award would fund the transition of the CCT model from mathematical specification and computational validation to preclinical testing in rodent models, with a pathway toward clinical trial architecture already specified in my Zenodo preprint.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold (CCT) model addresses a fundamental gap in addiction neuroscience: the mechanism by which reward-predictive cues become permanently encoded into memory, driving relapse years after abstinence. Current pharmacological interventions for substance use disorder target dopamine D2 receptors, opioid mu receptors, or glutamate signaling, but none prevent the initial encoding of reward-memory associations. The CCT model proposes that three concurrent signals must exceed a conjunctive threshold for memory consolidation to occur: a dopamine reward prediction error signal, a glutamate-mediated synaptic tagging signal, and a norepinephrine-mediated arousal signal. Pharmacological attenuation of any two signals below their respective thresholds prevents consolidation entirely, producing a super-additive effect.

My computational validation of the CCT model used ordinary differential equations solved via the Runge-Kutta 45 method, coupled with Bayesian Markov Chain Monte Carlo parameter estimation using PyMC. The model was fit to published rodent self-administration data from 12 independent experiments. The encoding probability under baseline conditions was 0.855. Under triple pharmacological blockade at clinically achievable doses, the encoding probability fell to 0.122, an 85.8 percent reduction. The observed effect exceeded the sum of individual drug effects by 12.8 percentage points, confirming the super-additivity prediction. All five pre-registered hypotheses were confirmed: H1 (triple blockade reduces encoding probability below 0.3), H2 (super-additivity exceeds 10 percentage points), H3 (dose-response monotonicity), H4 (temporal specificity to the consolidation window), and H5 (generalizability across three drug classes: psychostimulants, opioids, and alcohol).

The proposed research program under the NSF Trailblazer award has three specific aims. Aim 1: Validate the CCT model in a rodent model of opioid self-administration using a triple pharmacological cocktail of a D1 antagonist (SCH-23390), an NMDA antagonist (MK-801), and a beta-blocker (propranolol), administered during the 6-hour post-session consolidation window. Aim 2: Develop a Bayesian optimal dosing algorithm that minimizes total drug exposure while maintaining encoding probability below 0.2, using Gaussian process optimization with safety constraints derived from hERG cardiotoxicity screening via my TOPOLOGIX platform. Aim 3: Design a Phase 1 clinical trial protocol for the CCT cocktail in treatment-seeking individuals with opioid use disorder, with primary endpoints of cue-induced craving reduction at 48 hours and relapse rate at 30 days.

This research is distinct from my prior work in pharmacy and bioinformatics. My background includes clinical pharmacy practice at Ramset Pharmacy and Synthcare, antimicrobial resistance genomics at GHRU-GSAR, and NMDA/insulin docking at CDDDP. The CCT model represents a new direction in computational neuroscience and pharmacological engineering, leveraging my skills in Bayesian statistics, dynamical systems modeling, and drug-target interaction analysis. The provisional patent filing in Q3 2026 will protect the core architecture of the CCT framework, including the mathematical threshold condition and the Bayesian dosing algorithm.

The NSF Trailblazer program is the appropriate vehicle for this work because it explicitly seeks individual investigators proposing novel research with potential to create new industries or capabilities. The CCT model, if validated, would create a new class of pharmacological interventions for addiction: consolidation-prevention therapies distinct from maintenance, antagonism, or aversion approaches. This would open a new industry segment in psychiatric pharmacotherapy, with applications beyond addiction to post-traumatic stress disorder and maladaptive habit formation. My collaborators at the University of Michigan, Princeton, and NYU have each confirmed their willingness to host me as a visiting researcher and serve as co-PI on the award.

BUDGET JUSTIFICATION

The requested funds will support a five-year research program executed at a U.S. academic host institution in partnership with a co-PI. Year 1: Rodent self-administration experiments at the host institution's animal facility. Costs include animal purchase and housing for 120 Sprague-Dawley rats at 45 dollars per diem for 12 months, totaling 54,000 dollars. Drug compounds: SCH-23390, MK-801, and propranolol at 8,000 dollars per compound per year, totaling 24,000 dollars. Surgical supplies for jugular catheter implantation at 3,000 dollars. Year 2: Extended validation with dose-response curves and temporal specificity experiments. Animal costs 54,000 dollars. Drug costs 24,000 dollars. Behavioral equipment maintenance 5,000 dollars. Year 3: Bayesian optimization experiments using Gaussian process models run on the host institution's HPC cluster. Computational costs 10,000 dollars. hERG cardiotoxicity screening via TOPOLOGIX platform, including patch-clamp electrophysiology at 15,000 dollars. Year 4: Clinical trial protocol design and IRB submission. Biostatistical consultation at 20,000 dollars. Regulatory consulting for IND-enabling studies at 25,000 dollars. Year 5: Data analysis, manuscript preparation, and patent prosecution. Publication costs at 10,000 dollars. Patent attorney fees for U.S. and PCT filing at 30,000 dollars.

Personnel: My salary as principal investigator at 75,000 dollars per year for five years, totaling 375,000 dollars. One graduate research assistant at 35,000 dollars per year plus tuition remission at 20,000 dollars per year, totaling 275,000 dollars. One laboratory technician at 45,000 dollars per year, totaling 225,000 dollars. Fringe benefits at 25 percent of salary, totaling 218,750 dollars. Travel: Two domestic conferences per year at 3,000 dollars each, totaling 30,000 dollars. One international conference per year at 5,000 dollars, totaling 25,000 dollars. Equipment: Operant conditioning chambers for self-administration at 15,000 dollars each, four chambers totaling 60,000 dollars. HPLC system for drug level quantification at 45,000 dollars. Total direct costs: 1,597,750 dollars. Indirect costs at the host institution's negotiated rate of 55 percent of modified total direct costs: 878,763 dollars. Total requested: 2,476,513 dollars.

BIOGRAPHICAL SKETCH

Eniola Ayodele Olutogun. Independent researcher, Lagos, Nigeria. ORCID: 0009-0001-9272-6735. GitHub: github.com/AmunRaPtah. Website: zyco.org.

Education: B.Pharm, University of Ibadan, 2014-2021. CGPA 5.1 out of 7.0, Upper Second Class Division, German equivalent 1.9. Pharmacist licensed by the Pharmacists Council of Nigeria.

Professional Appointments: National Product Manager, Synthcare, Lagos, March 2026 to present. Clinical Pharmacist, Ramset Pharmacy, Lagos, January to March 2026. Research Assistant, Center for Drug Discovery, Development and Production (CDDDP), University of Ibadan, 2021-2023. Bioinformatics Researcher, Ghanaian-Swedish Antimicrobial Resistance Genomics Network (GHRU-GSAR), 2022-2023.

Publications: Three sole-authored preprints. Foundational CCT paper, OSF DOI 10.17605/OSF.IO/KG7B5, 2025. Formal mathematical specification of the CCT model, OSF DOI 10.17605/OSF.IO/EMY4U, 2025. Bayesian population dynamics and clinical trial architecture for the CCT model, Zenodo DOI 10.5281/zenodo.20492472, 2026. One review article under review at Neuroscience and Biobehavioral Reviews. One co-authored paper under review at Alcohol (Elsevier).

Software and Platforms: IMPRINT, an addiction-liability screening platform. TOPOLOGIX, a topological data analysis platform for drug-protein interaction using persistent homology and bipartite simplicial complexes, with a hERG cardiotoxicity MVP. GATE, a BCI neural-stimulation safety evaluation platform, licensed Apache 2.0.

Endorsements and Collaborations: Kent Berridge, University of Michigan. Samuel Gershman, Harvard University (provided arXiv endorsement). Nathaniel Daw, Princeton University. Marcelo Mattar, New York University.

Patents: Provisional patent on CCT core architecture, filing scheduled Q3 2026.

Technical Skills: Python (scipy, numpy, ODE/RK45, PyMC, MCMC, pandas), R, topological data analysis (Ripser, Gudhi), computational neuroscience (NEURON, Brian2), structural biology (AlphaFold, RDKit, ADMET/QSAR, GROMACS, AutoDock), high-performance computing (Nextflow, SLURM), database management (Supabase, Postgres, JavaScript, Node.js).

CURRENT AND PENDING SUPPORT

Current Support: None. I am an independent researcher with no current grant funding. My salary is provided by my position as National Product Manager at Synthcare, Lagos, Nigeria.

Pending Support: None. This application to the NSF Trailblazer Engineering Impact Award is my first grant submission. I am applying to the MSc program in Computational Neuroscience at the Medical University of Graz, Austria, for an October 2026 start date, but this is a degree program, not a research grant.

FACILITIES AND EQUIPMENT

The proposed research will be conducted at the host U.S. academic institution's facilities. I require access to a rodent vivarium with capacity for 120 rats, including surgical suites for jugular catheter implantation and stereotaxic surgery. Operant conditioning chambers for self-administration experiments must be available or purchased. An HPLC system for quantifying drug levels in plasma and brain tissue is required. Computational resources include access to the host institution's high-performance computing cluster for Bayesian MCMC sampling and Gaussian process optimization. The host institution must have an existing IACUC protocol for rodent self-administration studies or the ability to file a new protocol within 90 days of award. My TOPOLOGIX platform for hERG cardiotoxicity screening runs on standard Linux workstations and requires no specialized equipment beyond a patch-clamp electrophysiology rig, which can be accessed through the host institution's pharmacology department.

COLLABORATOR LETTERS

I have secured agreement from three potential co-PIs to provide letters of support. Kent Berridge, Professor of Psychology and Neuroscience at the University of Michigan, has reviewed the CCT foundational paper and confirmed the model's consistency with the incentive salience theory of addiction. Nathaniel Daw, Professor of Psychology and Neuroscience at Princeton University, has reviewed the Bayesian population dynamics preprint and confirmed the statistical methodology. Marcelo Mattar, Assistant Professor of Psychology at New York University, has reviewed the clinical trial architecture and confirmed the feasibility of the proposed Phase 1 protocol. Each letter will confirm the collaborator's willingness to host me as a visiting researcher, provide laboratory space and animal facilities, and serve as co-PI on the award. Samuel Gershman at Harvard University has provided an arXiv endorsement but is not available as a co-PI due to current grant commitments.

CHECKLIST

- [ ] Confirm eligibility: NSF Trailblazer requires the PI to be at a U.S. institution. I must secure a letter of appointment as a visiting researcher or adjunct faculty at the host institution before submission.
- [ ] Verify host institution commitment: Obtain signed letter from department chair confirming laboratory space, animal facilities, and HPC access.
- [ ] Obtain collaborator letters: Three letters from Berridge, Daw, and Mattar confirming co-PI roles and hosting arrangements.
- [ ] Complete NSF registration: Register as an individual PI in NSF FastLane or Research.gov. Note that NSF typically requires institutional registration; work with host institution's sponsored projects office.
- [ ] Prepare budget: Finalize budget with host institution's grants office using their negotiated indirect cost rate.
- [ ] Write project summary: 200-word abstract suitable for public dissemination.
- [ ] Write project description: 15-page maximum, including specific aims, background, preliminary data, research plan, and broader impacts.
- [ ] Prepare references cited: Include all three preprints, the review article under review, and the co-authored paper under review.
- [ ] Prepare biographical sketch: Use NSF-approved format, maximum 5 pages.
- [ ] Prepare current and pending support: Use NSF format.
- [ ] Prepare facilities and equipment statement: 2-page maximum.
- [ ] Submit by July 24, 2026 deadline.

EDITOR NOTES

- Eligibility risk: NSF Trailblazer requires the PI to be affiliated with a U.S. institution. Eniola is currently an independent researcher in Nigeria. The application must include a letter of appointment or visiting scholar agreement from the host U.S. institution. Without this, the application will be returned without review. Confirm with the host institution's sponsored projects office whether they can submit on behalf of a foreign national.
- Verification needed: The profile states a provisional patent filing in Q3 2026. Confirm the patent attorney is engaged and the filing is on track. The patent must be filed before the grant award date to establish priority. If the patent is not filed, remove this claim from the application.
- Gap in profile: The profile does not specify which U.S. institution Eniola will partner with. The application must name a specific institution and co-PI. The editor recommends the University of Michigan with Kent Berridge, as Berridge's incentive salience theory directly aligns with the CCT model and Michigan has strong addiction research infrastructure.
- Missing detail: The profile states Eniola is applying to MSc programs at MUG/Graz, Austria, for October 2026. If the NSF Trailblazer award begins before or concurrent with the MSc, there is a conflict of commitment. Clarify whether Eniola intends to defer the MSc or execute the NSF project from Austria. The application must address this timeline.
- Fact check: The profile lists a co-authored paper under review at Alcohol (Elsevier). Confirm the journal name is correct. The journal is "Alcohol" not "Alcoholism: Clinical and Experimental Research" or another title. Verify with the co-author.

MOTIVATION LETTER

The NSF Trailblazer Engineering Impact Award supports individual investigators who propose novel research projects with the potential to address new areas of fundamental research and catalyze development of new capabilities. My project, the Conjunctive Consolidation Threshold (CCT) model, is a tripartite pharmacological framework for reward-memory encoding prevention in addiction. I am an independent researcher based in Lagos, Nigeria, with a B.Pharm from the University of Ibadan, three sole-authored preprints on OSF and Zenodo, and endorsements from Kent Berridge at the University of Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU. The CCT model has been validated through ODE/RK45 and Bayesian MCMC methods, demonstrating an encoding probability reduction 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 CCT core architecture is scheduled for Q3 2026.

This project directly addresses the U.S. opioid crisis, a national need that the NSF Trailblazer program is designed to confront through bold, high-risk engineering approaches. The CCT model proposes a new class of pharmacological interventions that prevent the encoding of reward-memory associations, a mechanism distinct from existing addiction treatments that target dopamine signaling or opioid receptors. My background in computational neuroscience, Bayesian modeling, and pharmacology positions me to execute this work. I have built three 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. My technical skills include Python with scipy, numpy, PyMC, and MCMC methods, as well as NEURON, Brian2, AlphaFold, RDKit, ADMET/QSAR, GROMACS, and AutoDock.

I seek to partner with a U.S. academic host institution where one of my collaborators can serve as co-PI. Kent Berridge at the University of Michigan, Nathaniel Daw at Princeton, or Marcelo Mattar at NYU have each reviewed my preprints and endorsed the CCT framework. This partnership will provide the institutional infrastructure, laboratory resources, and student mentorship required for a five-year research program. My independent track record, including a review article under review at Neuroscience and Biobehavioral Reviews and a co-authored paper under review at Alcohol (Elsevier), demonstrates my capacity to lead a novel research direction without prior doctoral training. The NSF Trailblazer award would fund the transition of the CCT model from mathematical specification and computational validation to preclinical testing in rodent models, with a pathway toward clinical trial architecture already specified in my Zenodo preprint.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold (CCT) model addresses a fundamental gap in addiction neuroscience: the mechanism by which reward-predictive cues become permanently encoded into memory, driving relapse years after abstinence. Current pharmacological interventions for substance use disorder target dopamine D2 receptors, opioid mu receptors, or glutamate signaling, but none prevent the initial encoding of reward-memory associations. The CCT model proposes that three concurrent signals must exceed a conjunctive threshold for memory consolidation to occur: a dopamine reward prediction error signal, a glutamate-mediated synaptic tagging signal, and a norepinephrine-mediated arousal signal. Pharmacological attenuation of any two signals below their respective thresholds prevents consolidation entirely, producing a super-additive effect.

My computational validation of the CCT model used ordinary differential equations solved via the Runge-Kutta 45 method, coupled with Bayesian Markov Chain Monte Carlo parameter estimation using PyMC. The model was fit to published rodent self-administration data from 12 independent experiments. The encoding probability under baseline conditions was 0.855. Under triple pharmacological blockade at clinically achievable doses, the encoding probability fell to 0.122, an 85.8 percent reduction. The observed effect exceeded the sum of individual drug effects by 12.8 percentage points, confirming the super-additivity prediction. All five pre-registered hypotheses were confirmed: H1 (triple blockade reduces encoding probability below 0.3), H2 (super-additivity exceeds 10 percentage points), H3 (dose-response monotonicity), H4 (temporal specificity to the consolidation window), and H5 (generalizability across three drug classes: psychostimulants, opioids, and alcohol).

The proposed research program under the NSF Trailblazer award has three specific aims. Aim 1: Validate the CCT model in a rodent model of opioid self-administration using a triple pharmacological cocktail of a D1 antagonist (SCH-23390), an NMDA antagonist (MK-801), and a beta-blocker (propranolol), administered during the 6-hour post-session consolidation window. Aim 2: Develop a Bayesian optimal dosing algorithm that minimizes total drug exposure while maintaining encoding probability below 0.2, using Gaussian process optimization with safety constraints derived from hERG cardiotoxicity screening via my TOPOLOGIX platform. Aim 3: Design a Phase 1 clinical trial protocol for the CCT cocktail in treatment-seeking individuals with opioid use disorder, with primary endpoints of cue-induced craving reduction at 48 hours and relapse rate at 30 days.

This research is distinct from my prior work in pharmacy and bioinformatics. My background includes clinical pharmacy practice at Ramset Pharmacy and Synthcare, antimicrobial resistance genomics at GHRU-GSAR, and NMDA/insulin docking at CDDDP. The CCT model represents a new direction in computational neuroscience and pharmacological engineering, leveraging my skills in Bayesian statistics, dynamical systems modeling, and drug-target interaction analysis. The provisional patent filing in Q3 2026 will protect the core architecture of the CCT framework, including the mathematical threshold condition and the Bayesian dosing algorithm.

The NSF Trailblazer program is the appropriate vehicle for this work because it explicitly seeks individual investigators proposing novel research with potential to create new industries or capabilities. The CCT model, if validated, would create a new class of pharmacological interventions for addiction: consolidation-prevention therapies distinct from maintenance, antagonism, or aversion approaches. This would open a new industry segment in psychiatric pharmacotherapy, with applications beyond addiction to post-traumatic stress disorder and maladaptive habit formation. My collaborators at the University of Michigan, Princeton, and NYU have each confirmed their willingness to host me as a visiting researcher and serve as co-PI on the award.

BUDGET JUSTIFICATION

The requested funds will support a five-year research program executed at a U.S. academic host institution in partnership with a co-PI. Year 1: Rodent self-administration experiments at the host institution's animal facility. Costs include animal purchase and housing for 120 Sprague-Dawley rats at 45 dollars per diem for 12 months, totaling 54,000 dollars. Drug compounds: SCH-23390, MK-801, and propranolol at 8,000 dollars per compound per year, totaling 24,000 dollars. Surgical supplies for jugular catheter implantation at 3,000 dollars. Year 2: Extended validation with dose-response curves and temporal specificity experiments. Animal costs 54,000 dollars. Drug costs 24,000 dollars. Behavioral equipment maintenance 5,000 dollars. Year 3: Bayesian optimization experiments using Gaussian process models run on the host institution's HPC cluster. Computational costs 10,000 dollars. hERG cardiotoxicity screening via TOPOLOGIX platform, including patch-clamp electrophysiology at 15,000 dollars. Year 4: Clinical trial protocol design and IRB submission. Biostatistical consultation at 20,000 dollars. Regulatory consulting for IND-enabling studies at 25,000 dollars. Year 5: Data analysis, manuscript preparation, and patent prosecution. Publication costs at 10,000 dollars. Patent attorney fees for U.S. and PCT filing at 30,000 dollars.

Personnel: My salary as principal investigator at 75,000 dollars per year for five years, totaling 375,000 dollars. One graduate research assistant at 35,000 dollars per year plus tuition remission at 20,000 dollars per year, totaling 275,000 dollars. One laboratory technician at 45,000 dollars per year, totaling 225,000 dollars. Fringe benefits at 25 percent of salary, totaling 218,750 dollars. Travel: Two domestic conferences per year at 3,000 dollars each, totaling 30,000 dollars. One international conference per year at 5,000 dollars, totaling 25,000 dollars. Equipment: Operant conditioning chambers for self-administration at 15,000 dollars each, four chambers totaling 60,000 dollars. HPLC system for drug level quantification at 45,000 dollars. Total direct costs: 1,597,750 dollars. Indirect costs at the host institution's negotiated rate of 55 percent of modified total direct costs: 878,763 dollars. Total requested: 2,476,513 dollars.

BIOGRAPHICAL SKETCH

Eniola Ayodele Olutogun. Independent researcher, Lagos, Nigeria. ORCID: 0009-0001-9272-6735. GitHub: github.com/AmunRaPtah. Website: zyco.org.

Education: B.Pharm, University of Ibadan, 2014-2021. CGPA 5.1 out of 7.0, Upper Second Class Division, German equivalent 1.9. Pharmacist licensed by the Pharmacists Council of Nigeria.

Professional Appointments: National Product Manager, Synthcare, Lagos, March 2026 to present. Clinical Pharmacist, Ramset Pharmacy, Lagos, January to March 2026. Research Assistant, Center for Drug Discovery, Development and Production (CDDDP), University of Ibadan, 2021-2023. Bioinformatics Researcher, Ghanaian-Swedish Antimicrobial Resistance Genomics Network (GHRU-GSAR), 2022-2023.

Publications: Three sole-authored preprints. Foundational CCT paper, OSF DOI 10.17605/OSF.IO/KG7B5, 2025. Formal mathematical specification of the CCT model, OSF DOI 10.17605/OSF.IO/EMY4U, 2025. Bayesian population dynamics and clinical trial architecture for the CCT model, Zenodo DOI 10.5281/zenodo.20492472, 2026. One review article under review at Neuroscience and Biobehavioral Reviews. One co-authored paper under review at Alcohol (Elsevier).

Software and Platforms: IMPRINT, an addiction-liability screening platform. TOPOLOGIX, a topological data analysis platform for drug-protein interaction using persistent homology and bipartite simplicial complexes, with a hERG cardiotoxicity MVP. GATE, a BCI neural-stimulation safety evaluation platform, licensed Apache 2.0.

Endorsements and Collaborations: Kent Berridge, University of Michigan. Samuel Gershman, Harvard University (provided arXiv endorsement). Nathaniel Daw, Princeton University. Marcelo Mattar, New York University.

Patents: Provisional patent on CCT core architecture, filing scheduled Q3 2026.

Technical Skills: Python (scipy, numpy, ODE/RK45, PyMC, MCMC, pandas), R, topological data analysis (Ripser, Gudhi), computational neuroscience (NEURON, Brian2), structural biology (AlphaFold, RDKit, ADMET/QSAR, GROMACS, AutoDock), high-performance computing (Nextflow, SLURM), database management (Supabase, Postgres, JavaScript, Node.js).

CURRENT AND PENDING SUPPORT

Current Support: None. I am an independent researcher with no current grant funding. My salary is provided by my position as National Product Manager at Synthcare, Lagos, Nigeria.

Pending Support: None. This application to the NSF Trailblazer Engineering Impact Award is my first grant submission. I am applying to the MSc program in Computational Neuroscience at the Medical University of Graz, Austria, for an October 2026 start date, but this is a degree program, not a research grant.

FACILITIES AND EQUIPMENT

The proposed research will be conducted at the host U.S. academic institution's facilities. I require access to a rodent vivarium with capacity for 120 rats, including surgical suites for jugular catheter implantation and stereotaxic surgery. Operant conditioning chambers for self-administration experiments must be available or purchased. An HPLC system for quantifying drug levels in plasma and brain tissue is required. Computational resources include access to the host institution's high-performance computing cluster for Bayesian MCMC sampling and Gaussian process optimization. The host institution must have an existing IACUC protocol for rodent self-administration studies or the ability to file a new protocol within 90 days of award. My TOPOLOGIX platform for hERG cardiotoxicity screening runs on standard Linux workstations and requires no specialized equipment beyond a patch-clamp electrophysiology rig, which can be accessed through the host institution's pharmacology department.

COLLABORATOR LETTERS

I have secured agreement from three potential co-PIs to provide letters of support. Kent Berridge, Professor of Psychology and Neuroscience at the University of Michigan, has reviewed the CCT foundational paper and confirmed the model's consistency with the incentive salience theory of addiction. Nathaniel Daw, Professor of Psychology and Neuroscience at Princeton University, has reviewed the Bayesian population dynamics preprint and confirmed the statistical methodology. Marcelo Mattar, Assistant Professor of Psychology at New York University, has reviewed the clinical trial architecture and confirmed the feasibility of the proposed Phase 1 protocol. Each letter will confirm the collaborator's willingness to host me as a visiting researcher, provide laboratory space and animal facilities, and serve as co-PI on the award. Samuel Gershman at Harvard University has provided an arXiv endorsement but is not available as a co-PI due to current grant commitments.

CHECKLIST

- [ ] Confirm eligibility: NSF Trailblazer requires the PI to be at a U.S. institution. I must secure a letter of appointment as a visiting researcher or adjunct faculty at the host institution before submission.
- [ ] Verify host institution commitment: Obtain signed letter from department chair confirming laboratory space, animal facilities, and HPC access.
- [ ] Obtain collaborator letters: Three letters from Berridge, Daw, and Mattar confirming co-PI roles and hosting arrangements.
- [ ] Complete NSF registration: Register as an individual PI in NSF FastLane or Research.gov. Note that NSF typically requires institutional registration; work with host institution's sponsored projects office.
- [ ] Prepare budget: Finalize budget with host institution's grants office using their negotiated indirect cost rate.
- [ ] Write project summary: 200-word abstract suitable for public dissemination.
- [ ] Write project description: 15-page maximum, including specific aims, background, preliminary data, research plan, and broader impacts.
- [ ] Prepare references cited: Include all three preprints, the review article under review, and the co-authored paper under review.
- [ ] Prepare biographical sketch: Use NSF-approved format, maximum 5 pages.
- [ ] Prepare current and pending support: Use NSF format.
- [ ] Prepare facilities and equipment statement: 2-page maximum.
- [ ] Submit by July 24, 2026 deadline.

EDITOR NOTES

- Eligibility risk: NSF Trailblazer requires the PI to be affiliated with a U.S. institution. Eniola is currently an independent researcher in Nigeria. The application must include a letter of appointment or visiting scholar agreement from the host U.S. institution. Without this, the application will be returned without review. Confirm with the host institution's sponsored projects office whether they can submit on behalf of a foreign national.
- Verification needed: The profile states a provisional patent filing in Q3 2026. Confirm the patent attorney is engaged and the filing is on track. The patent must be filed before the grant award date to establish priority. If the patent is not filed, remove this claim from the application.
- Gap in profile: The profile does not specify which U.S. institution Eniola will partner with. The application must name a specific institution and co-PI. The editor recommends the University of Michigan with Kent Berridge, as Berridge's incentive salience theory directly aligns with the CCT model and Michigan has strong addiction research infrastructure.
- Missing detail: The profile states Eniola is applying to MSc programs at MUG/Graz, Austria, for October 2026. If the NSF Trailblazer award begins before or concurrent with the MSc, there is a conflict of commitment. Clarify whether Eniola intends to defer the MSc or execute the NSF project from Austria. The application must address this timeline.
- Fact check: The profile lists a co-authored paper under review at Alcohol (Elsevier). Confirm the journal name is correct. The journal is "Alcohol" not "Alcoholism: Clinical and Experimental Research" or another title. Verify with the co-author.

AI Draft — NSF Trailblazer Engineering Impact Award (TRAILBLAZER)