01Pancreatic Dysregulation
Investigating molecular signals associated with dysfunction and biological stress within the pancreas.
Advancing Precision Diagnostics Through Clinical Research
Kihealth collaborates with leading academic medical centers, healthcare systems, and clinical investigators to validate next-generation molecular diagnostics for earlier disease detection, risk stratification, and precision medicine.
Why Clinical Research Matters
Evidence Is the Bridge Between Molecular Discovery and Clinical Practice
A promising biomarker can reveal something important about disease biology—but discovery alone is not enough. Before a molecular signal can meaningfully support research or patient care, it must be studied across relevant populations, compared with established clinical measures and evaluated over time.
Clinical research determines whether a biomarker is reproducible, biologically meaningful and capable of answering an important clinical or scientific question.
What Clinical Research Makes Possible
01
Establish Biological Meaning
Determine what a molecular signal represents, how it relates to active disease biology and how it changes across different stages of disease.
02
Demonstrate Clinical Relevance
Evaluate whether the biomarker is associated with established measures, meaningful outcomes, disease progression or treatment response.
03
Support Translation
Generate the evidence required to advance promising discoveries toward clinical validation, diagnostic development, therapeutic research and future regulatory pathways.
Who Is Impacted
Patients and Research Participants
Stronger evidence can support earlier visibility into biological change, more precise disease classification and more informed approaches to monitoring and treatment.
Physicians
Clinically validated biomarkers may provide additional information to support risk assessment, referral, follow-up and patient-management decisions.
Researchers and Academic Institutions
Integrated biomarker and clinical data can deepen the understanding of disease mechanisms and generate new hypotheses for further study.
Therapeutic Developers
Biomarkers can support participant identification, study stratification, biological-response assessment and the development of more targeted clinical trials.
Healthcare Systems and Laboratories
Well-validated diagnostics can help translate emerging science into scalable, reproducible and clinically responsible testing.
The Bigger Impact
Better evidence leads to better questions, more informative studies and a clearer path from biological discovery to meaningful application.
Clinical research is how scientific potential becomes trusted knowledge.
The Case for Better Evidence
Better Diagnostics Can Change the Course of Disease, and Therapeutic Development
When disease biology becomes measurable, researchers can design more informative studies, therapeutic developers can select and stratify participants more precisely, and physicians may gain better tools for identifying and monitoring disease. Clinical research is what turns that potential into credible evidence.
Metabolic Disease
21%
Lower Mortality
Among people diagnosed with diabetes during a large Danish screening program, screening and earlier treatment were associated with a 21% reduction in all-cause mortality and a 16% reduction in cardiovascular events.
Detecting metabolic disease earlier can create an opportunity to intervene before cardiovascular and other irreversible complications develop.
ADDITION-Denmark controlled study
Neurodegenerative Disease
10–20 Years
Before Symptoms
Alzheimer’s-related biological changes can begin 10 to 20 years before clinical symptoms lead to a diagnosis. During that time, neuronal injury and disease progression may already be occurring.
Neurodegenerative disease does not begin when symptoms appear. Better biomarkers could move detection into the years when more function remains, patients may have greater access to early-stage treatments, and researchers have a better opportunity to intervene before irreversible neurological damage accumulates.
Alzheimer’s disease progression literature
Cancer
4.75M
Deaths Averted
Prevention and screening accounted for an estimated 4.75 million deaths averted across breast, cervical, colorectal, lung and prostate cancers between 1975 and 2020—approximately 80% of the deaths averted in the analysis.
Earlier detection and prevention can change cancer outcomes at population scale, often before advanced treatment becomes necessary.
National Cancer Institute
Why Biomarkers Matter
Biomarker-guided programs succeed at roughly twice the rate
Biomarkers can support participant selection, trial enrichment, dose selection, safety assessment and measurement of therapeutic response—helping create more focused studies and reducing uncertainty in drug development.
The FDA states that properly used biomarkers may enable leaner, more focused clinical trials and potentially reduce development time and cost while maintaining patient protections.FDA Biomarker Qualification Program
Phase I → Approval
Likelihood of a development program reaching approval
With preselection biomarkers15.9%
Without biomarkers7.6%
BIO/Informa/QLS, 2011–2020 development programs
Phase II → Phase III
Observed rate of advancing to the next phase
With preselection biomarkers46.3%
Without biomarkers28.3%
BIO/Informa/QLS, 2011–2020 development programs
The opportunity is larger than a single test.
Better clinical evidence can strengthen diagnostic development, improve therapeutic research and help move healthcare toward earlier, more biologically informed intervention.
Statistics describe broader healthcare and drug-development trends and do not represent outcomes achieved by Kihealth products or research programs.
Our Research Mission
Connecting Biological Discovery to Clinical Utility
Kihealth Labs conducts clinical research to determine how emerging biomarkers can reveal active disease biology, identify risk earlier and improve the development of diagnostics and precision therapeutics.
Our objective is not simply to identify biomarkers, but to establish when, where and how they can meaningfully support research and clinical decision-making.
Five objectives
01
Detect active disease biology
Surface molecular signals that reflect ongoing pathological processes before they manifest clinically.
02
Identify risk before irreversible damage
Recognize the window where intervention can still alter the disease trajectory and preserve function.
03
Improve participant stratification
Segment populations by biological subtype and risk to enable more targeted, efficient study design.
04
Track biological change over time
Follow longitudinal biomarker trajectories to reveal disease progression and response dynamics.
05
Evaluate treatment response
Quantify whether and how rapidly a therapeutic is altering the underlying biology, not just symptoms.
Research Focus
What We Study
Our research examines the biological processes underlying metabolic disease—from organ-level dysfunction and cellular injury to systemic metabolic change, disease progression and therapeutic response.
01
02Beta-Cell Death
Studying biomarkers associated with the injury and loss of insulin-producing pancreatic beta cells.
03Beta-Cell Function and Reserve
Evaluating the capacity of remaining beta cells to produce and release insulin in response to metabolic demand.
04Systemic Metabolic Function
Examining the interconnected roles of the pancreas, liver, skeletal muscle, adipose tissue and circulating metabolic signals.
05Insulin Resistance
Studying how effectively the body responds to insulin and how impaired signaling contributes to metabolic dysfunction.
06Disease Progression
Using longitudinal biomarkers to understand how biological dysfunction changes before and during the development of overt disease.
07Treatment Response
Evaluating whether an intervention produces a measurable change in the underlying biology—not only in downstream clinical measurements.
08Patient Stratification
Investigating whether integrated biomarker patterns can identify distinct biological profiles, risk levels or potential response groups.
Together, these research areas provide a multidimensional view of metabolic health—from cellular injury to whole-body function and longitudinal change.
Focus Areas
Research capabilities and biomarker applications vary by program. Certain assays and applications remain under development or are available for research use only.
Research Focus Areas
The scientific frontiers we study
Our research spans the full spectrum of metabolic and oncologic disease biology, from molecular discovery through longitudinal clinical monitoring.
Type 1 Diabetes
Twelve scientific frontiers, one molecular foundation — every program connects back to the same blood-based signals and the same commitment to earlier, more precise intervention.
12Focus
areas
areas
Current Clinical Studies
Active and forthcoming research programs
Kihealth Labs' study portfolio spans early feasibility work, prospective analytical and clinical validation, and longitudinal cohorts designed to generate durable clinical evidence.
Type 1 Diabetes / Beta Cell Biology
RecruitingPediatric Beta Cell Health Study
Study Design
Prospective, multi-center observational cohort
Enrollment Target
Target: 100 pediatric participants
Collaborating Institutions
Nemours Children's Hospital
Disease Area
Type 1 Diabetes / Beta Cell Biology
Objectives
To characterize beta-cell death following Stage 3 T1D onset in pediatric patients and evaluate its relationship to residual beta-cell function and disease progression.
Primary Endpoints
- Longitudinal change in circulating beta cell death signal
- Association with autoantibody status and glycemic markers
- Time-to-clinical T1D in high-risk stratum
TYPE 2 DIABETES
ActiveBeta Intercept™ Clinical Validation Program
Study Design
Multi-cohort analytical and clinical validation study
Enrollment Target
Target: 500 adult and pediatric participants
Collaborating Institutions
Academic diabetes centers and reference laboratories
Disease Area
TYPE 2 DIABETES
Objectives
Establish the analytical performance and clinical validity of the Beta Intercept™ blood-based beta cell health assay across diverse patient populations and clinical contexts.
Primary Endpoints
- Analytical sensitivity, specificity, precision, and reproducibility
- Clinical sensitivity vs reference standards
- Cross-site reproducibility across CLIA-grade laboratories
Prediabetes / Metabolic Disease
In DevelopmentLongitudinal Metabolic Monitoring Study
Study Design
Prospective longitudinal cohort with quarterly biomarker sampling
Enrollment Target
Target: 200 adults with metabolic risk factors
Collaborating Institutions
Health system partners across multiple regions
Disease Area
Prediabetes / Metabolic Disease
Objectives
Evaluate whether serial molecular biomarker monitoring can detect metabolic disease progression earlier than traditional glycemic and lipid markers.
Primary Endpoints
- Time-to-detection of metabolic transition vs standard care
- Trajectory modeling of beta cell and hepatic signals
- Concordance with continuous glucose and metabolic phenotyping
Pancreatic Cancer / High-Risk Surveillance
PlanningPancreatic Cancer Biomarker Feasibility Study
Study Design
Prospective feasibility study in high-risk surveillance cohorts
Enrollment Target
Target: 300 high-risk adults
Collaborating Institutions
Comprehensive cancer centers with active pancreatic surveillance programs including Anschutz in Colorado
Disease Area
Pancreatic Cancer / High-Risk Surveillance
Objectives
Assess the feasibility of a blood-based liquid biopsy approach for early detection signal in individuals under active pancreatic surveillance.
Primary Endpoints
- Assay performance in high-risk surveillance context
- Concordance with EUS/MRI surveillance findings
- Operational feasibility across surveillance sites
Type 1 Diabetes
ActiveDAISY: Beta-Cell cfDNA Early Detection
Study Design
Observational cohort across T1D stages
Enrollment Target
DAISY (Diabetes Autoimmunity Study in the Young) cohort
Collaborating Institutions
DAISY study network
Disease Area
Type 1 Diabetes
Objectives
Determine whether beta-cell cfDNA identifies progressive beta-cell injury across Stages 1–3 T1D.
Primary Endpoints
- Beta-cell cfDNA levels by T1D stage
- Association with progression to Stage 3 T1D
- Diagnostic performance versus controls
Type 1 Diabetes
ActiveTEDDY: cfDNA Progression Biomarker
Study Design
Longitudinal observational cohort in genetically at-risk children
Enrollment Target
TEDDY (The Environmental Determinants of Diabetes in the Young) cohort
Collaborating Institutions
TEDDY study network
Disease Area
Type 1 Diabetes
Objectives
Evaluate whether beta-cell cfDNA predicts T1D progression in genetically at-risk children.
Primary Endpoints
- Longitudinal change in beta-cell cfDNA
- Association with islet-autoantibody development
- Association with progression to Stage 2 or Stage 3 T1D
Type 1 Diabetes
PendingBeta Intercept™ T1D Validation Extension
Study Design
Clinical validation study across early and recently diagnosed T1D
Enrollment Target
Participants with Stage 1, 2, and 3 T1D
Collaborating Institutions
TrialNet
Disease Area
Type 1 Diabetes
Objectives
Validate the Beta Intercept™ assay in participants with early or recently diagnosed T1D stages 1, 2, and 3.
Primary Endpoints
- Difference in beta-cell-death signal versus controls
- Correlation with stimulated C-peptide
- Assay sensitivity, specificity and reproducibility
Pancreatic Cancer
PendingMultiomic Liquid Biopsy: PDAC
Study Design
Multiomic signature discovery and validation study
Enrollment Target
Pancreatic cancer, new-onset diabetes, and high-risk control participants
Collaborating Institutions
University of Colorado Anschutz
Disease Area
Pancreatic Cancer
Objectives
Identify a blood-based multiomic signature that distinguishes pancreatic cancer from new-onset diabetes and high-risk controls.
Primary Endpoints
- Identification of a reproducible PDAC biomarker signature
- Sensitivity and specificity for detecting PDAC
- Classification performance versus new-onset diabetes and controls
Biospecimen Cohort Development
ActiveHuman and De-Identified Biospecimens
Study Design
Biospecimen cohort assembly for assay development and analytical validation
Enrollment Target
Qualified specimens across multiple specimen types
Collaborating Institutions
Kihealth Labs Biobank
Disease Area
Biospecimen Cohort Development
Objectives
Establish fit-for-purpose biospecimen cohorts for assay development and analytical validation.
Primary Endpoints
- Number of qualified specimens collected
- Specimen quality and analyte stability
- Assay success and reproducibility across specimen types
Biospecimen Cohort Development
ActiveDe-Identified Residual Testing Samples
Study Design
Residual clinical sample feasibility and validation study
Enrollment Target
Residual clinical samples meeting eligibility criteria
Collaborating Institutions
Kihealth Labs Biobank
Disease Area
Biospecimen Cohort Development
Objectives
Evaluate the feasibility of using residual clinical samples for biomarker research and assay validation.
Primary Endpoints
- Percentage of samples meeting eligibility and quality criteria
- Successful biomarker detection rate
- Concordance across repeat measurements
Type 1 Diabetes
EnrollingUSF/Tampa General: INS cfDNA in New-Onset T1D
Study Design
Prospective study in newly diagnosed Stage 3 T1D patients
Enrollment Target
Newly diagnosed Stage 3 T1D patients and controls
Collaborating Institutions
USF / Tampa General Hospital
Disease Area
Type 1 Diabetes
Objectives
Confirm beta-cell cfDNA elevation in patients with newly diagnosed Stage 3 T1D.
Primary Endpoints
- Difference in beta-cell cfDNA versus controls
- Correlation with time from diagnosis
- Association with residual beta-cell function
Research Collaborations
Flexible models for advancing clinical research
Kihealth Labs works with academic institutions, healthcare organizations and therapeutic developers through research models tailored to each program’s scientific objectives, available samples and stage of development.
Academic Research Collaborations
Joint studies with university and academic medical center investigators to explore biomarker biology and disease mechanisms.
Retrospective Biobank Studies
Analysis of existing, well-characterized sample cohorts to validate biomarker performance against known clinical outcomes.
Prospective Observational Studies
Longitudinal studies tracking biomarker change over time in at-risk populations ahead of overt disease.
Interventional-Trial Biomarker Studies
Biomarker endpoints embedded within therapeutic trials to measure biological response to an intervention.
Pharmaceutical Biomarker Programs
Diagnostic development partnerships supporting drug development, patient stratification and treatment response.
Pilot Studies with Healthcare & Private-Sector Partners
Targeted pilots with health systems and industry partners to evaluate feasibility and clinical utility in real-world settings.
Each engagement is scoped around sample availability, endpoints and regulatory pathway. Partnership structures are outlined in detail on our partnerships page.
Explore Research Partnerships Scientific Evidence
Research designed to be examined, shared and built upon
Clinical Utility of a Multiplex ddPCR Assay for Differentially Methylated INS cfDNA
Method and clinical rationale for quantifying beta-cell death from a single blood draw using multiplex droplet digital PCR.
- Authors
- Kihealth Labs Scientific Team
- Date
- 2025
- Source
- Kihealth Labs
Beta Intercept™ Clinical Evidence Summary
Consolidated summary of analytical and clinical performance data supporting the Beta Intercept™ assay.
- Authors
- Kihealth Labs Clinical Affairs
- Date
- 2025
- Source
- Kihealth Labs
Teplizumab Study — Comparative Analysis Summary
Comparative analysis of unmethylated INS cfDNA dynamics in relation to teplizumab immunotherapy in at-risk individuals.
- Authors
- Kihealth Labs with academic collaborators
- Date
- 2025
- Source
- Academic collaboration
cfDNA Quantification in Beta-Cell / Islet Infusion Recipients
Circulating cell-free DNA quantified with Kihealth's ddPCR methylation assay in samples from islet infusion recipients.
- Authors
- Kihealth Labs Research Team
- Date
- 2025
- Source
- Transplant research cohort
Scientific Background and Clinical Precedence for Beta-Cell Derived cfDNA
Review of the published evidence base establishing liquid-biopsy detection of tissue-specific cell death.
- Authors
- Kihealth Labs Scientific Team
- Date
- 2025
- Source
- Kihealth Labs
ADA Innovation of the Year Award 2025 — Program Presentation
Turning beta-cell death into a real-time endpoint: the award program presentation on a first-of-its-kind biomarker quantifying active beta-cell apoptosis for earlier endpoints, improved patient stratification and more accurate assessment of therapeutic efficacy.
- Authors
- Jaroch M, Barbalho P, Anderson J, Mons R, Benson M, Cucoranu I, Morris C
- Date
- 2025
- Source
- American Diabetes Association — Scientific Sessions
ADA 2026 Clinical Poster Presentation
Latest clinical poster presented at the American Diabetes Association 2026 scientific sessions, showcasing Kihealth's most recent data on beta-cell death biomarkers and their application to early detection and therapeutic monitoring in type 1 diabetes.
- Authors
- Kihealth Labs Research Team
- Date
- 2026
- Source
- American Diabetes Association — Scientific Sessions
Research Network
A collaborative network built for rigorous evidence generation
Our research is conducted in partnership with the institutions that see patients, run laboratories, and shape clinical practice — each contributing a distinct capability to the evidence base.
Academic Medical Centers
Children's Hospitals
Healthcare Systems
Clinical Research Sites
Reference Laboratories
Industry Partners
Kihealth Labs
Academic Medical Centers
Investigator-led studies with access to deeply phenotyped patient cohorts.
Children's Hospitals
Pediatric endocrinology programs following at-risk and newly diagnosed patients.
Healthcare Systems
Real-world feasibility and clinical-utility pilots inside routine care pathways.
Clinical Research Sites
Protocol execution, consent and standardized longitudinal sample collection.
Reference Laboratories
Cross-site assay comparability, proficiency testing and method transfer.
Industry Partners
Therapeutic developers embedding biomarker endpoints into trial designs.
4+
Active clinical studies
6
Partner categories
Multi-site
Sample sourcing
CLIA-ready
Assay workflow
Responsible Research
Scientific Rigor at Every Stage
Kihealth Labs is committed to conducting and supporting research with appropriate scientific oversight, participant protections, data stewardship and transparent communication of findings.
06Pillars
Six pillars of research governance framework the operational, ethical, and scientific standards upheld across every Kihealth Labs program.
Governed by institutional review · IRB oversight · CLIA-aligned laboratory practice
Governance RegisterSection R-01
01 / 06
Ethical Oversight
ComplianceResearch is conducted under applicable institutional and ethical-review requirements.
02 / 06
Informed Consent
ConsentParticipant consent requirements are defined according to the study design, institution and intended use of samples and data.
03 / 06
Privacy and De-Identification
PrivacyParticipant information and biospecimens are handled using appropriate privacy and de-identification practices.
04 / 06
Data Security
SecurityResearch data are managed through controlled systems and program-appropriate security practices.
05 / 06
Laboratory Quality
QualityTesting and biospecimen workflows follow documented laboratory procedures and quality controls.
06 / 06
Research Integrity
IntegrityFindings are communicated with appropriate context, limitations and distinctions between research and established clinical use.
Document maintained by the Office of Research GovernanceRev. 2026
Participate in Research
Build the evidence base for the next generation of precision diagnostics.
Kihealth Labs partners with investigators, healthcare systems, academic researchers, and pharmaceutical and biotechnology companies to design and execute clinical studies that meet the highest standards of scientific and regulatory rigor.
Investigators•Healthcare Systems•Academic Researchers•Pharmaceutical Companies•Biotechnology Partners