BCF–TOGFLACA Drug Discovery & Human Model Research Software

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Summary

BCF–TOGFLACA is an exploratory computational drug-discovery research platform using the Bioscale Computational Formula (BCF). It supports structured investigation of viral diseases and cancer through disease-reference analysis, candidate drug-source and active pharmaceutical ingredient (API) correspondence testing, and proposed human-model validation pathways. Its outputs are research hypotheses requiring independent biomedical verification.

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About this innovation

BCF–TOGFLACA Drug Discovery & Human Model Research Software is an exploratory biomedical research platform developed using the Bioscale Computational Formula (BCF). The software is designed to investigate computational relationships among disease references, potential drug sources, active pharmaceutical ingredients (APIs), proposed biological targets, and experimental research pathways. Research Scope The current prototype contains two principal research domains: 1. Antiviral Research The antiviral component focuses on selected diseases associated with the Togaviridae and Flaviviridae virus families. It provides computational procedures for organizing disease references, candidate drug sources, APIs, and proposed molecular or biological research mechanisms. 2. Cancer and Oncology Research The oncology component extends the computational framework to selected cancer research programs. It uses structured disease references to investigate possible numerical correspondence among candidate natural-product sources, APIs, proposed cancer-cell targets, and research mechanisms. Computational Research Methodology BCF–TOGFLACA employs structured reference calculations, generational numerical analysis, correspondence testing, candidate tracking, and computational verification procedures. Its workflow distinguishes disease references, candidate source materials, APIs, proposed targets, and research evidence. The system is intended to provide reproducible computational observations and organized research hypotheses for further investigation. Human-Model Research Pathway The software includes research-planning provisions for evaluating hypotheses using appropriate human-relevant experimental systems, potentially including primary tumour cells, patient-derived organoids, cancer cell lines, organ-on-chip models, and ex vivo tissue systems. These represent proposed research pathways rather than completed experimental validations. Research Integrity and Scientific Validation BCF–TOGFLACA does not establish that numerical correspondence proves a biological mechanism, therapeutic activity, safety, or clinical efficacy. Any promising computational observation requires independent scientific investigation, including relevant laboratory studies, biological assays, toxicological assessment, experimental reproducibility, and regulatory oversight where applicable. Innovation and Potential Application The proposed innovation is a structured computational platform for organizing early-stage drug-discovery hypotheses and documenting candidate relationships before further experimental evaluation. Its potential applications include academic research, exploratory pharmaceutical investigation, natural-product screening, oncology research planning, antiviral research planning, and collaborations with qualified biomedical research institutions. The software remains a research prototype and is not a clinically validated diagnostic or therapeutic system.

BCF–TOGFLACA: Drug Discovery & Human Model Research Software

OCIIP Support Assistance — Project Description and Budget
Project owner: Rahali Lawali
Project: Bioscale Computational Formula — TOGFLACA
Proposed funding target: ₦7,000,000
Proposed implementation period: Seven months
1. Project description BCF–TOGFLACA is a computational research software project intended to support the structured organisation and prioritisation of research candidates involving Togaviridae, Flaviviridae and cancer-related research workflows. The software brings together defined computational references, disease and source correspondence, candidate/API identification, target verification, proposed-mechanism organisation, evidence capture and planning for appropriate human-model research. The proposed project will strengthen software engineering, computational verification, independent scientific review, reference-data organisation, research-planning documentation and pilot evaluation. The software is a research-support platform. Its outputs do not, by themselves, establish therapeutic efficacy, safety or clinical suitability. Laboratory and human-model validation remain separate scientific activities requiring appropriate expertise, facilities, protocols and approvals.

2. Objectives
1. Improve software reliability and integration of research workflows.
2. Test computational procedures and document reproducibility.
3. Obtain independent biomedical and pharmacological review.
4. Improve the organisation and traceability of supporting scientific evidence.
5. Document research requirements, evidence gaps and next-stage validation needs.
6. Produce a technical report identifying completed work and outstanding limitations.

3. Proposed budget | Expenditure category | Amount | |---|---:|
|Software engineering, workflow integration and defect correction | ₦1,500,000 |
| Computational verification and reproducibility testing | ₦750,000 |
| Independent biomedical and pharmacological expert review | ₦1,000,000 |
| Scientific literature, reference data and evidence organisation | ₦600,000 |
| Interface improvements, data handling and security measures | ₦700,000 |
| Research protocols and human-model validation planning | ₦650,000 |
| Technical documentation and research reporting | ₦400,000 |
| Pilot evaluation, feedback and corrective development | ₦500,000 |
| Hosting, software tools and secure backup | ₦350,000 |
| Contingency for approved, unforeseen project costs | ₦550,000 |
|Total requested| ₦7,000,000 |

4. Proposed milestones -Months 1–2: Workflow engineering and computational testing.
- Months 2–3: Independent scientific review and evidence-gap assessment.
- Months 3–4: Candidate, target and source workflow evaluation.
- Months 4–5: Research and human-model validation planning.
- Months 5–6: Pilot evaluation and software corrections.
- Months 6–7: Technical documentation and final assessment.

5. Expected deliverables - Updated software prototype and computational test records. - Independent scientific-review comments and an evidence-gap register. - Documented candidate, target and source workflow tests. - Research-planning documentation for subsequent validation. - Pilot-evaluation and corrective-development reports. - Final technical report identifying limitations and next-stage requirements.

6. Accountability Expenditure will be tracked against approved budget categories, with supporting quotations, invoices, receipts, payment records and evidence of services or work products. Milestone records will distinguish software development, literature-based research, expert review and research planning. The project will not represent computational prioritisation as proof of efficacy or safety, nor imply that laboratory, animal or clinical validation has occurred unless independently documented.

🎯 The Problem

Early-stage drug-discovery research involves large volumes of disease information, biological targets, candidate drug sources, active pharmaceutical ingredients, and experimental evidence. Organizing these components into a transparent, reproducible research workflow can be challenging, particularly for independent researchers and resource-constrained research settings. Candidate selection may also suffer from fragmented documentation, poorly defined comparison criteria, and inadequate traceability between the original research question and proposed experimental procedures. BCF–TOGFLACA addresses the computational organization aspect of this problem by providing a structured environment for disease-reference analysis, candidate source and API correspondence testing, hypothesis documentation, and proposed experimental validation planning. The software does not replace established biomedical screening, pharmacology, molecular biology, toxicology, or clinical research. Its purpose is to provide an additional exploratory computational framework whose usefulness must be established through independent testing and scientific collaboration.

💡 The Solution

BCF–TOGFLACA provides an integrated computational research environment that connects disease-reference inputs with structured candidate drug-source, active pharmaceutical ingredient (API), and proposed biological-target investigations. The platform incorporates two research domains: Antiviral Drug-Discovery Research: Computational investigation of selected Togaviridae and Flaviviridae disease programs, including candidate source and API correspondence testing. Cancer and Oncology Research: Computational investigation of selected cancer programs using structured reference hierarchies, candidate source and API analysis, proposed cancer-target features, and human-model research planning. The software provides numerical verification procedures, source–API tracking, research-status documentation, and exportable records intended to support scientific review. A central feature is the separation of computational hypotheses from experimentally established biomedical findings. The proposed development pathway involves collaboration with qualified scientific institutions to evaluate reproducibility, biological relevance, experimental performance, and possible research applications. The long-term objective is to develop BCF–TOGFLACA into a scientifically evaluated computational research-support platform that can complement established early-stage drug-discovery methods.