Draft — Integrated Data Systems & Services (IDSS)

MOTIVATION LETTER

The Conjunctive Consolidation Threshold model, a tripartite pharmacological framework for reward-memory encoding prevention, has been validated through ODE/RK45 and Bayesian MCMC methods to reduce encoding probability from 0.855 to 0.122, an 85.8 percent reduction with super-additivity of 12.8 percentage points. This model, along with three platforms I built independently in Lagos, Nigeria, constitutes a novel data cyberinfrastructure for addiction research. The Integrated Data Systems and Services programme at the National Science Foundation funds foundational, multi-disciplinary systems that serve broad research communities. My CCT model, IMPRINT screening tool, TOPOLOGIX topological data analysis platform, and GATE neural-stimulation safety evaluator together form exactly such a system.

I am an independent researcher based in Lagos, Nigeria, with a B.Pharm from the University of Ibadan and provisional patent protection on the CCT core architecture filed in Q3 2026. My work has received endorsements from Kent Berridge at the University of Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at New York University. Gershman provided my arXiv endorsement. A review article on the CCT framework is under review at Neuroscience and Biobehavioral Reviews, and a co-authored paper is under review at Alcohol. All five pre-registered hypotheses H1 through H5 were confirmed.

The IDSS programme requires proposals that integrate data, methods, and systems across disciplines. My platforms do this. IMPRINT screens addiction liability using pharmacokinetic and pharmacodynamic parameters. TOPOLOGIX applies persistent homology and bipartite simplicial complexes to drug-protein interaction data, with a validated MVP for hERG cardiotoxicity prediction. GATE evaluates brain-computer interface neural-stimulation safety under an Apache 2.0 license. These tools are open-source, built with Python, PyMC, Gudhi, Ripser, and RDKit, and run on Nextflow and SLURM for HPC scalability.

I seek a partnership with a U.S.-based principal investigator at a university with cyberinfrastructure expertise. My contribution would be the CCT model, the three platforms, and the computational pharmacology domain knowledge. The U.S. PI would provide institutional eligibility, access to NSF cyberinfrastructure resources, and integration with existing data systems. Together, we would propose a national-scale data cyberinfrastructure for addiction research that serves neuroscientists, pharmacologists, and data scientists.

My career trajectory is early-career, pre-PhD, and LMIC-track. I am applying for MSc programmes beginning October 2026 at the Medical University of Graz in Austria. The IDSS grant would fund my independent research during this transition period, supporting computational resources, data storage, and collaboration travel. Nigeria has no national addiction data infrastructure. This project would build one.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold model addresses a fundamental gap in addiction neuroscience: the mechanism by which reward-memory associations become encoded during a discrete temporal window following reward exposure. Current pharmacological interventions target either reward signaling or memory consolidation separately. The CCT model posits that these processes converge at a conjunctive threshold, and that simultaneous, sub-threshold modulation of both pathways produces super-additive prevention of encoding.

I formalized this model mathematically in a preprint on OSF with DOI 10.17605/OSF.IO/EMY4U. The model consists of three coupled ordinary differential equations representing dopamine D1 receptor activation, NMDA receptor-mediated calcium influx, and cAMP response element-binding protein phosphorylation. The system was solved using RK45 integration with adaptive step sizing. Bayesian parameter estimation was performed using PyMC with Markov chain Monte Carlo sampling across four chains of 10,000 iterations each. Posterior predictive checks confirmed model fit to published rodent self-administration data.

The key result: simultaneous administration of a sub-threshold D1 antagonist and a sub-threshold NMDA antagonist at a specific temporal offset of 15 minutes post-reward reduces encoding probability from 0.855 to 0.122. This 85.8 percent reduction exceeds the sum of individual effects by 12.8 percentage points, confirming super-additivity. The full Bayesian population dynamics and clinical trial architecture is published on Zenodo with DOI 10.5281/zenodo.20492472.

This model is not theoretical only. I built three platforms that operationalize it. IMPRINT screens compounds for addiction liability by simulating their effect on CCT parameters. TOPOLOGIX uses topological data analysis, specifically persistent homology on bipartite simplicial complexes, to predict drug-protein interactions relevant to the CCT pathways. The hERG cardiotoxicity MVP achieved an AUROC of 0.634 on a held-out test set of 200 compounds. GATE evaluates the safety of neural-stimulation protocols used in brain-computer interfaces, ensuring that stimulation parameters do not inadvertently trigger reward-memory encoding.

For the IDSS programme, I propose to integrate these three platforms into a unified data cyberinfrastructure. The system would ingest pharmacological data from public databases, run CCT simulations, screen compounds, predict off-target interactions, and evaluate stimulation safety, all through a single API. The backend uses Supabase and Postgres for data storage, Python for computation, and Nextflow for workflow orchestration on HPC clusters. The frontend is built with JavaScript and Node.js.

The infrastructure would serve multiple research communities. Neuroscientists would use it to test hypotheses about reward-memory encoding. Pharmacologists would screen compounds before animal studies. Data scientists would access the open-source code and datasets for method development. The system would be released under an Apache 2.0 license, consistent with my existing GATE platform.

Nigeria has no national addiction data infrastructure. The country has a growing opioid crisis, particularly tramadol and codeine misuse among young adults aged 18 to 35. My platforms were built in Lagos using publicly available data and open-source tools. They are designed for low-resource settings. The IDSS grant would allow me to scale this infrastructure, add cloud computing resources, and establish data-sharing protocols with Nigerian research institutions.

I have the technical skills to execute this project. My GitHub repository at github.com/AmunRaPtah contains the full CCT simulation code, the TOPOLOGIX pipeline, and the GATE safety evaluator. I am proficient in Python with scipy, numpy, PyMC, and pandas; R for statistical analysis; Gudhi and Ripser for topological data analysis; NEURON and Brian2 for neural simulation; AlphaFold and RDKit for structural biology; GROMACS and AutoDock for molecular dynamics; and Nextflow and SLURM for HPC workflow management. I have experience with ADMET and QSAR modeling from my work at the Centre for Drug Discovery, Development and Production at the University of Ibadan.

The provisional patent on the CCT core architecture, filed in Q3 2026, protects the commercial potential of this framework. The patent covers the method of simultaneous sub-threshold modulation of D1 and NMDA receptors at a specific temporal offset. This intellectual property would be managed through the U.S. partner institution under standard NSF intellectual property policies.

PROJECT DESCRIPTION

The proposed project, titled "A National-Scale Data Cyberinfrastructure for Addiction Research: Integrating the Conjunctive Consolidation Threshold Model with Open-Source Computational Platforms," addresses the IDSS programme's goal of supporting foundational, multi-disciplinary data systems. The project has three components: data integration, platform unification, and community deployment.

Data integration: The system will ingest pharmacological data from PubChem, ChEMBL, DrugBank, and the NIMH Psychoactive Drug Screening Program. It will also accept user-uploaded data in standard formats. All data will be stored in a Supabase Postgres database with standardized schemas for compound properties, protein targets, binding affinities, pharmacokinetic parameters, and stimulation protocols. Data provenance will be tracked using versioned entries with timestamps and source identifiers.

Platform unification: IMPRINT, TOPOLOGIX, and GATE will be refactored into modular microservices communicating through a REST API. IMPRINT will accept a compound SMILES string and return addiction liability scores based on CCT simulation. TOPOLOGIX will accept a protein sequence and return persistent homology features and predicted interaction partners. GATE will accept a stimulation protocol and return safety metrics including CCT activation probability. The unified system will allow chained queries: a user could submit a compound, receive its addiction liability score, see its predicted off-target interactions, and evaluate whether a stimulation protocol could counteract its effects.

Community deployment: The system will be released as open-source software under Apache 2.0. A public instance will run on NSF-funded cloud infrastructure. Documentation, tutorials, and example notebooks will be provided. A workshop will be held at a major conference, such as the Society for Neuroscience annual meeting or the Computational and Systems Neuroscience meeting, to train researchers in using the infrastructure.

The project timeline is 24 months. Months 1 through 6: data integration and database design. Months 7 through 12: platform refactoring and API development. Months 13 through 18: testing, validation, and documentation. Months 19 through 24: community deployment, workshop, and publication.

The budget request is for computational resources, including cloud computing credits for HPC workloads and data storage; personnel support for the PI and a graduate student at the U.S. partner institution; travel for collaboration and conference attendance; and publication costs for open-access journals.

BUDGET JUSTIFICATION

Computational resources: 50,000 dollars for cloud computing credits on NSF-supported platforms such as Jetstream2 or Bridges-2. These credits will support Bayesian MCMC sampling for CCT parameter estimation, persistent homology calculations for TOPOLOGIX, and molecular dynamics simulations for validation studies. Estimated compute time: 100,000 core-hours per year.

Personnel: 30,000 dollars for partial salary support for the U.S.-based principal investigator, covering 0.5 months per year. 25,000 dollars for a graduate research assistant at the U.S. institution, covering 3 months per year. The graduate student will assist with API development and documentation.

Travel: 10,000 dollars for two trips per year between Lagos and the U.S. partner institution for collaboration. 5,000 dollars for conference attendance to present results and conduct the workshop.

Publication: 5,000 dollars for open-access publication fees in journals such as PLOS Computational Biology or eLife.

Total: 125,000 dollars.

BIOGRAPHICAL SKETCH

Eniola Ayodele Olutogun. Independent researcher, Lagos, Nigeria. B.Pharm, University of Ibadan, 2021. CGPA 5.1 out of 7.0, German equivalent 1.9. Licensed pharmacist, Pharmacists Council of Nigeria.

Professional appointments: National Product Manager, Synthcare, March 2026 to present. Clinical Pharmacist, Ramset Pharmacy, January to March 2026. Research Assistant, Centre for Drug Discovery, Development and Production, University of Ibadan, 2021 to 2022. Bioinformatics Researcher, Ghanaian-South African Genomics Research Hub for Antimicrobial Resistance, 2022 to 2023.

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

Software: IMPRINT addiction liability screening platform. TOPOLOGIX topological data analysis platform for drug-protein interactions. GATE BCI neural-stimulation safety evaluation platform, Apache 2.0 license. All code available at github.com/AmunRaPtah.

Endorsements: Kent Berridge, University of Michigan. Samuel Gershman, Harvard University. Nathaniel Daw, Princeton University. Marcelo Mattar, New York University.

Intellectual property: Provisional patent on CCT core architecture, filed Q3 2026.

DATA MANAGEMENT PLAN

All data generated by this project will be made publicly available through the NSF-supported data repositories. Pharmacological data ingested from public databases will be cited with their original identifiers. Derived data, including CCT simulation outputs, persistent homology features, and safety metrics, will be deposited in Zenodo with DOIs. Code will be maintained on GitHub under the Apache 2.0 license. Documentation will be hosted on Read the Docs. A data dictionary describing all variables, units, and formats will be provided.

Data will be stored on NSF cloud infrastructure during the project period. After project completion, data will be transferred to a long-term repository such as the NSF Data Repository or a domain-specific repository like the Neuroscience Information Framework. Data will be retained for a minimum of 10 years after project completion.

No personally identifiable information or protected health information will be collected. All data are from public databases or generated by simulation.

BROADER IMPACTS

This project will build addiction research capacity in Nigeria, a country with no national addiction data infrastructure. The open-source platforms will be freely available to Nigerian researchers, clinicians, and policymakers. The project will train one graduate student at the U.S. partner institution in computational pharmacology and data cyberinfrastructure. The workshop at a major conference will train additional researchers. The project will produce educational materials, including tutorials and example notebooks, that can be used in university courses.

The CCT model has potential clinical applications for preventing addiction in patients receiving opioid or stimulant medications. The IMPRINT screening tool could be used by pharmaceutical companies to identify compounds with addiction liability before clinical trials. The TOPOLOGIX platform could be applied to other drug-target interaction problems beyond addiction. The GATE platform could be used by BCI developers to ensure patient safety.

The project will contribute to the NSF's goal of advancing science and engineering in underrepresented regions. Nigeria is the most populous country in Africa, with a growing scientific workforce but limited research infrastructure. This project will demonstrate that high-quality computational research can be conducted from Lagos using open-source tools and cloud computing.

CHECKLIST

- [ ] Identify a U.S.-based principal investigator at a university with cyberinfrastructure expertise to serve as lead institution
- [ ] Confirm that the U.S. PI is eligible to submit to NSF IDSS programme
- [ ] Draft a letter of collaboration from the U.S. PI confirming their role and institutional commitment
- [ ] Obtain letters of endorsement from Kent Berridge, Samuel Gershman, Nathaniel Daw, and Marcelo Mattar
- [ ] Prepare a detailed budget with justification, total 125,000 dollars
- [ ] Write a data management plan following NSF guidelines
- [ ] Compile a biographical sketch for Eniola Ayodele Olutogun
- [ ] Compile a biographical sketch for the U.S. PI
- [ ] Prepare a project description not exceeding 15 pages
- [ ] Submit the proposal through Research.gov by July 28, 2026
- [ ] Verify that the proposal is submitted under Category II
- [ ] Confirm that the proposal references NSF programme solicitation NSF 26-509

EDITOR NOTES

- Eligibility risk: Eniola cannot be the PI on an NSF grant because he is not affiliated with a U.S. institution. The proposal must be submitted by a U.S.-based PI. Eniola would be listed as a co-PI or senior personnel. Confirm that NSF allows non-U.S. citizens as co-PIs on IDSS grants. If not, Eniola would be a consultant or collaborator without salary support from NSF funds.

- The budget of 125,000 dollars is an estimate. The IDSS programme does not specify a maximum budget, but Category II submissions typically range from 100,000 to 500,000 dollars. Eniola should confirm the budget range with the U.S. PI and adjust accordingly.

- The provisional patent on the CCT core architecture was filed in Q3 2026. Eniola should verify the exact filing date and patent application number. NSF requires disclosure of any intellectual property that could affect the project. The patent should be managed through the U.S. partner institution's technology transfer office.

- Eniola's ORCID is 0009-0001-9272-6735. He should ensure that his ORCID profile is up to date with all publications, preprints, and software repositories. NSF increasingly uses ORCID for biographical sketches.

- The project timeline assumes that Eniola will begin the MSc programme at the Medical University of Graz in October 2026. If the grant is awarded before that date, Eniola will need to clarify his institutional affiliation during the grant period. He could be listed as an independent researcher with a subcontract to the U.S. institution, or he could transfer the grant to his MSc institution. Discuss this with the U.S. PI and the NSF programme officer.

MOTIVATION LETTER

The Conjunctive Consolidation Threshold model, a tripartite pharmacological framework for reward-memory encoding prevention, has been validated through ODE/RK45 and Bayesian MCMC methods to reduce encoding probability from 0.855 to 0.122, an 85.8 percent reduction with super-additivity of 12.8 percentage points. This model, along with three platforms I built independently in Lagos, Nigeria, constitutes a novel data cyberinfrastructure for addiction research. The Integrated Data Systems and Services programme at the National Science Foundation funds foundational, multi-disciplinary systems that serve broad research communities. My CCT model, IMPRINT screening tool, TOPOLOGIX topological data analysis platform, and GATE neural-stimulation safety evaluator together form exactly such a system.

I am an independent researcher based in Lagos, Nigeria, with a B.Pharm from the University of Ibadan and provisional patent protection on the CCT core architecture filed in Q3 2026. My work has received endorsements from Kent Berridge at the University of Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at New York University. Gershman provided my arXiv endorsement. A review article on the CCT framework is under review at Neuroscience and Biobehavioral Reviews, and a co-authored paper is under review at Alcohol. All five pre-registered hypotheses H1 through H5 were confirmed.

The IDSS programme requires proposals that integrate data, methods, and systems across disciplines. My platforms do this. IMPRINT screens addiction liability using pharmacokinetic and pharmacodynamic parameters. TOPOLOGIX applies persistent homology and bipartite simplicial complexes to drug-protein interaction data, with a validated MVP for hERG cardiotoxicity prediction. GATE evaluates brain-computer interface neural-stimulation safety under an Apache 2.0 license. These tools are open-source, built with Python, PyMC, Gudhi, Ripser, and RDKit, and run on Nextflow and SLURM for HPC scalability.

I seek a partnership with a U.S.-based principal investigator at a university with cyberinfrastructure expertise. My contribution would be the CCT model, the three platforms, and the computational pharmacology domain knowledge. The U.S. PI would provide institutional eligibility, access to NSF cyberinfrastructure resources, and integration with existing data systems. Together, we would propose a national-scale data cyberinfrastructure for addiction research that serves neuroscientists, pharmacologists, and data scientists.

My career trajectory is early-career, pre-PhD, and LMIC-track. I am applying for MSc programmes beginning October 2026 at the Medical University of Graz in Austria. The IDSS grant would fund my independent research during this transition period, supporting computational resources, data storage, and collaboration travel. Nigeria has no national addiction data infrastructure. This project would build one.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold model addresses a fundamental gap in addiction neuroscience: the mechanism by which reward-memory associations become encoded during a discrete temporal window following reward exposure. Current pharmacological interventions target either reward signaling or memory consolidation separately. The CCT model posits that these processes converge at a conjunctive threshold, and that simultaneous, sub-threshold modulation of both pathways produces super-additive prevention of encoding.

I formalized this model mathematically in a preprint on OSF with DOI 10.17605/OSF.IO/EMY4U. The model consists of three coupled ordinary differential equations representing dopamine D1 receptor activation, NMDA receptor-mediated calcium influx, and cAMP response element-binding protein phosphorylation. The system was solved using RK45 integration with adaptive step sizing. Bayesian parameter estimation was performed using PyMC with Markov chain Monte Carlo sampling across four chains of 10,000 iterations each. Posterior predictive checks confirmed model fit to published rodent self-administration data.

The key result: simultaneous administration of a sub-threshold D1 antagonist and a sub-threshold NMDA antagonist at a specific temporal offset of 15 minutes post-reward reduces encoding probability from 0.855 to 0.122. This 85.8 percent reduction exceeds the sum of individual effects by 12.8 percentage points, confirming super-additivity. The full Bayesian population dynamics and clinical trial architecture is published on Zenodo with DOI 10.5281/zenodo.20492472.

This model is not theoretical only. I built three platforms that operationalize it. IMPRINT screens compounds for addiction liability by simulating their effect on CCT parameters. TOPOLOGIX uses topological data analysis, specifically persistent homology on bipartite simplicial complexes, to predict drug-protein interactions relevant to the CCT pathways. The hERG cardiotoxicity MVP achieved an AUROC of 0.634 on a held-out test set of 200 compounds. GATE evaluates the safety of neural-stimulation protocols used in brain-computer interfaces, ensuring that stimulation parameters do not inadvertently trigger reward-memory encoding.

For the IDSS programme, I propose to integrate these three platforms into a unified data cyberinfrastructure. The system would ingest pharmacological data from public databases, run CCT simulations, screen compounds, predict off-target interactions, and evaluate stimulation safety, all through a single API. The backend uses Supabase and Postgres for data storage, Python for computation, and Nextflow for workflow orchestration on HPC clusters. The frontend is built with JavaScript and Node.js.

The infrastructure would serve multiple research communities. Neuroscientists would use it to test hypotheses about reward-memory encoding. Pharmacologists would screen compounds before animal studies. Data scientists would access the open-source code and datasets for method development. The system would be released under an Apache 2.0 license, consistent with my existing GATE platform.

Nigeria has no national addiction data infrastructure. The country has a growing opioid crisis, particularly tramadol and codeine misuse among young adults aged 18 to 35. My platforms were built in Lagos using publicly available data and open-source tools. They are designed for low-resource settings. The IDSS grant would allow me to scale this infrastructure, add cloud computing resources, and establish data-sharing protocols with Nigerian research institutions.

I have the technical skills to execute this project. My GitHub repository at github.com/AmunRaPtah contains the full CCT simulation code, the TOPOLOGIX pipeline, and the GATE safety evaluator. I am proficient in Python with scipy, numpy, PyMC, and pandas; R for statistical analysis; Gudhi and Ripser for topological data analysis; NEURON and Brian2 for neural simulation; AlphaFold and RDKit for structural biology; GROMACS and AutoDock for molecular dynamics; and Nextflow and SLURM for HPC workflow management. I have experience with ADMET and QSAR modeling from my work at the Centre for Drug Discovery, Development and Production at the University of Ibadan.

The provisional patent on the CCT core architecture, filed in Q3 2026, protects the commercial potential of this framework. The patent covers the method of simultaneous sub-threshold modulation of D1 and NMDA receptors at a specific temporal offset. This intellectual property would be managed through the U.S. partner institution under standard NSF intellectual property policies.

PROJECT DESCRIPTION

The proposed project, titled "A National-Scale Data Cyberinfrastructure for Addiction Research: Integrating the Conjunctive Consolidation Threshold Model with Open-Source Computational Platforms," addresses the IDSS programme's goal of supporting foundational, multi-disciplinary data systems. The project has three components: data integration, platform unification, and community deployment.

Data integration: The system will ingest pharmacological data from PubChem, ChEMBL, DrugBank, and the NIMH Psychoactive Drug Screening Program. It will also accept user-uploaded data in standard formats. All data will be stored in a Supabase Postgres database with standardized schemas for compound properties, protein targets, binding affinities, pharmacokinetic parameters, and stimulation protocols. Data provenance will be tracked using versioned entries with timestamps and source identifiers.

Platform unification: IMPRINT, TOPOLOGIX, and GATE will be refactored into modular microservices communicating through a REST API. IMPRINT will accept a compound SMILES string and return addiction liability scores based on CCT simulation. TOPOLOGIX will accept a protein sequence and return persistent homology features and predicted interaction partners. GATE will accept a stimulation protocol and return safety metrics including CCT activation probability. The unified system will allow chained queries: a user could submit a compound, receive its addiction liability score, see its predicted off-target interactions, and evaluate whether a stimulation protocol could counteract its effects.

Community deployment: The system will be released as open-source software under Apache 2.0. A public instance will run on NSF-funded cloud infrastructure. Documentation, tutorials, and example notebooks will be provided. A workshop will be held at a major conference, such as the Society for Neuroscience annual meeting or the Computational and Systems Neuroscience meeting, to train researchers in using the infrastructure.

The project timeline is 24 months. Months 1 through 6: data integration and database design. Months 7 through 12: platform refactoring and API development. Months 13 through 18: testing, validation, and documentation. Months 19 through 24: community deployment, workshop, and publication.

The budget request is for computational resources, including cloud computing credits for HPC workloads and data storage; personnel support for the PI and a graduate student at the U.S. partner institution; travel for collaboration and conference attendance; and publication costs for open-access journals.

BUDGET JUSTIFICATION

Computational resources: 50,000 dollars for cloud computing credits on NSF-supported platforms such as Jetstream2 or Bridges-2. These credits will support Bayesian MCMC sampling for CCT parameter estimation, persistent homology calculations for TOPOLOGIX, and molecular dynamics simulations for validation studies. Estimated compute time: 100,000 core-hours per year.

Personnel: 30,000 dollars for partial salary support for the U.S.-based principal investigator, covering 0.5 months per year. 25,000 dollars for a graduate research assistant at the U.S. institution, covering 3 months per year. The graduate student will assist with API development and documentation.

Travel: 10,000 dollars for two trips per year between Lagos and the U.S. partner institution for collaboration. 5,000 dollars for conference attendance to present results and conduct the workshop.

Publication: 5,000 dollars for open-access publication fees in journals such as PLOS Computational Biology or eLife.

Total: 125,000 dollars.

BIOGRAPHICAL SKETCH

Eniola Ayodele Olutogun. Independent researcher, Lagos, Nigeria. B.Pharm, University of Ibadan, 2021. CGPA 5.1 out of 7.0, German equivalent 1.9. Licensed pharmacist, Pharmacists Council of Nigeria.

Professional appointments: National Product Manager, Synthcare, March 2026 to present. Clinical Pharmacist, Ramset Pharmacy, January to March 2026. Research Assistant, Centre for Drug Discovery, Development and Production, University of Ibadan, 2021 to 2022. Bioinformatics Researcher, Ghanaian-South African Genomics Research Hub for Antimicrobial Resistance, 2022 to 2023.

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

Software: IMPRINT addiction liability screening platform. TOPOLOGIX topological data analysis platform for drug-protein interactions. GATE BCI neural-stimulation safety evaluation platform, Apache 2.0 license. All code available at github.com/AmunRaPtah.

Endorsements: Kent Berridge, University of Michigan. Samuel Gershman, Harvard University. Nathaniel Daw, Princeton University. Marcelo Mattar, New York University.

Intellectual property: Provisional patent on CCT core architecture, filed Q3 2026.

DATA MANAGEMENT PLAN

All data generated by this project will be made publicly available through the NSF-supported data repositories. Pharmacological data ingested from public databases will be cited with their original identifiers. Derived data, including CCT simulation outputs, persistent homology features, and safety metrics, will be deposited in Zenodo with DOIs. Code will be maintained on GitHub under the Apache 2.0 license. Documentation will be hosted on Read the Docs. A data dictionary describing all variables, units, and formats will be provided.

Data will be stored on NSF cloud infrastructure during the project period. After project completion, data will be transferred to a long-term repository such as the NSF Data Repository or a domain-specific repository like the Neuroscience Information Framework. Data will be retained for a minimum of 10 years after project completion.

No personally identifiable information or protected health information will be collected. All data are from public databases or generated by simulation.

BROADER IMPACTS

This project will build addiction research capacity in Nigeria, a country with no national addiction data infrastructure. The open-source platforms will be freely available to Nigerian researchers, clinicians, and policymakers. The project will train one graduate student at the U.S. partner institution in computational pharmacology and data cyberinfrastructure. The workshop at a major conference will train additional researchers. The project will produce educational materials, including tutorials and example notebooks, that can be used in university courses.

The CCT model has potential clinical applications for preventing addiction in patients receiving opioid or stimulant medications. The IMPRINT screening tool could be used by pharmaceutical companies to identify compounds with addiction liability before clinical trials. The TOPOLOGIX platform could be applied to other drug-target interaction problems beyond addiction. The GATE platform could be used by BCI developers to ensure patient safety.

The project will contribute to the NSF's goal of advancing science and engineering in underrepresented regions. Nigeria is the most populous country in Africa, with a growing scientific workforce but limited research infrastructure. This project will demonstrate that high-quality computational research can be conducted from Lagos using open-source tools and cloud computing.

CHECKLIST

- [ ] Identify a U.S.-based principal investigator at a university with cyberinfrastructure expertise to serve as lead institution
- [ ] Confirm that the U.S. PI is eligible to submit to NSF IDSS programme
- [ ] Draft a letter of collaboration from the U.S. PI confirming their role and institutional commitment
- [ ] Obtain letters of endorsement from Kent Berridge, Samuel Gershman, Nathaniel Daw, and Marcelo Mattar
- [ ] Prepare a detailed budget with justification, total 125,000 dollars
- [ ] Write a data management plan following NSF guidelines
- [ ] Compile a biographical sketch for Eniola Ayodele Olutogun
- [ ] Compile a biographical sketch for the U.S. PI
- [ ] Prepare a project description not exceeding 15 pages
- [ ] Submit the proposal through Research.gov by July 28, 2026
- [ ] Verify that the proposal is submitted under Category II
- [ ] Confirm that the proposal references NSF programme solicitation NSF 26-509

EDITOR NOTES

- Eligibility risk: Eniola cannot be the PI on an NSF grant because he is not affiliated with a U.S. institution. The proposal must be submitted by a U.S.-based PI. Eniola would be listed as a co-PI or senior personnel. Confirm that NSF allows non-U.S. citizens as co-PIs on IDSS grants. If not, Eniola would be a consultant or collaborator without salary support from NSF funds.

- The budget of 125,000 dollars is an estimate. The IDSS programme does not specify a maximum budget, but Category II submissions typically range from 100,000 to 500,000 dollars. Eniola should confirm the budget range with the U.S. PI and adjust accordingly.

- The provisional patent on the CCT core architecture was filed in Q3 2026. Eniola should verify the exact filing date and patent application number. NSF requires disclosure of any intellectual property that could affect the project. The patent should be managed through the U.S. partner institution's technology transfer office.

- Eniola's ORCID is 0009-0001-9272-6735. He should ensure that his ORCID profile is up to date with all publications, preprints, and software repositories. NSF increasingly uses ORCID for biographical sketches.

- The project timeline assumes that Eniola will begin the MSc programme at the Medical University of Graz in October 2026. If the grant is awarded before that date, Eniola will need to clarify his institutional affiliation during the grant period. He could be listed as an independent researcher with a subcontract to the U.S. institution, or he could transfer the grant to his MSc institution. Discuss this with the U.S. PI and the NSF programme officer.

AI Draft — Integrated Data Systems & Services (IDSS)