Continuous N-of-1 Computational Feasibility Study of a Whole Genome Sequence (B2026N1)

Automated Hypothesis Generation Via Deterministic Bioenergetic Simulation of a Whole Genome Sequence: A Continuous N-of-1 Computational Feasibility Study

This is an observational, computational N-of-1 study that uses previously collected Whole Genome Sequencing (WGS) data from a single adult participant to evaluate the feasibility of a deterministic bioenergetic simulation model. The study does not involve clinical interventions, treatments, or prospective specimen collection. All analyses are performed on existing genomic data in a secure computational environment.

The purpose of this study is to determine whether a physics-based metabolic model can successfully integrate individual genomic constraints to generate personalized, hypothesis-driven insights about metabolic pathways. The study focuses on model feasibility and computational performance, not clinical outcomes. No medications, diets, or behavioral interventions are administered or evaluated.

Study Overview

• Status: Active, not recruiting
• Conditions: Computational Modeling of Individual Metabolic Pathways

Detailed Description

This protocol (B-2026-N1) describes a continuous, observational N-of-1 computational feasibility study conducted by Bioactify LLC and What Ifs Tech Inc. The study uses secondary, commercially obtained 30x Whole Genome Sequencing (WGS) data from a single adult participant. No new data are collected for research purposes, and no clinical interventions are performed.

The primary objective is to assess the feasibility of integrating static genomic constraints into a deterministic simulation engine that incorporates Flux Balance Analysis (FBA) and dynamic physiologically based modeling. The computational framework is designed to explore how individual genetic variants may influence metabolic pathway behavior. All analyses occur within an isolated cloud environment using pre-existing data.

This study is observational and exploratory. It does not evaluate the safety, efficacy, or clinical utility of any treatment, diet, medication, or device. The research aims to generate methodological insights about individualized computational modeling and hypothesis generation.

This study received an Exempt Research Determination from Pearl IRB (Protocol ID: 2026-0119) under 45 CFR 46.104(d)(4), as it involves only secondary use of existing data with no interaction or intervention with human subjects.

• Study Type: Observational
• Enrollment (Actual): 1

Contacts and Locations

Study Locations

• United States
  • New York
    • Wappingers Falls, New York, United States, 12590
      • Bioactify LLC

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Probability Sample

Study Population

Single adult participant providing previously collected Whole Genome Sequencing (WGS) data for observational, computational analysis. No recruitment or enrollment of additional participants.

Description

Inclusion Criteria:

• Adult female participant, age 45

  • Possesses previously collected 30x Whole Genome Sequencing (WGS) data
  • Able to provide self-reported phenotypic and lifestyle information as needed for computational analysis
  • Willing to participate in a self-directed, observational N-of-1 study

Exclusion Criteria:

• None

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
Single Participant; This cohort includes the single adult participant whose previously collected Whole Genome Sequencing (WGS) data will be used for computational analysis. No interventions, treatments, or clinical procedures are performed. All analyses are observational and based solely on secondary data.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Feasibility of Deterministic In Silico Metabolic Flux Simulation	Assesses whether secondary 30x Whole Genome Sequencing (WGS) data can be successfully ingested and processed by a deterministic computational framework that incorporates Flux Balance Analysis (FBA) and dynamic physiologically based modeling. Feasibility is defined by the ability to run simulations without system failure, data corruption, or computational instability. This outcome evaluates computational performance only and does not assess clinical endpoints.	3 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Generation of a Jacobian Sensitivity Atlas	Evaluates whether the simulation engine can successfully generate a differentiable sensitivity atlas that identifies potential enzymatic or transport constraints based solely on static genomic inputs. This outcome assesses algorithmic output quality and computational stability, not clinical or diagnostic interpretation.	3 months

Collaborators and Investigators

• Sponsor: Bioactify LLC
• Investigators: Principal Investigator: Esther Cashbaugh, Bioactify LLC

Study record dates

Study Major Dates

• Study Start (Actual): March 5, 2026
• Primary Completion (Estimated): March 1, 2027
• Study Completion (Estimated): March 1, 2027

Study Registration Dates

• First Submitted: March 5, 2026
• First Submitted That Met QC Criteria: March 5, 2026
• First Posted (Actual): March 10, 2026

Study Record Updates

• Last Update Posted (Actual): March 10, 2026
• Last Update Submitted That Met QC Criteria: March 5, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Keywords: N-of-1; Bioenergetics; Whole Genome Sequencing; Metabolic Pathways; Computational Modeling; Flux Balance Analysis; Genomic Simulation; Deterministic Modeling; Secondary Data Analysis
• Other Study ID Numbers: B-2026-N1

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Individual participant data will not be shared because the study includes a single participant and uses previously collected Whole Genome Sequencing (WGS) data that cannot be de-identified.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No