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OncoPredikt-HRD

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OncoPredikt-HRD

OncoPredikt-HRD

OncoPredikt-HRD1 is an AI-based assay which can predict HRD status using whole slide imaging analysis of the diagnostic H&E slide to identify Homologous Recombination Deficiency (HRD) to identify patient candidates likely to respond to PARPi therapy.
OncoPredikt-HRD is:
  • Ideal for HRD Screening Pharma Development
  • AI-Enabled Algorithm
  • Poster Session at ASCO 2022
Genetics Institute of America is currently offering this Laboratory Developed Test (LDT) for Pharma Development studies in a research capacity. Future development plans include launching the OncoPredikt-HRD assay to clinicians for the evaluation of HRD status in cancer patients.
The AI engine was first trained on TCGA datasets (1892 images)
WSI were randomly split into training and validation sets designated either HRD or HRP based on: BRCA1/2, HRR genes and previously generated aggregate combined HRD score from:
  • Loss of heterozygosity (LOH),
  • Large scale genomic instability(LST),
  • Telomeric allelic imbalance (TAI)
HRD Prediction Accuracy = 99.3%2
Published Sensitivity of 100%2
Published Specificity of 99%2

OncoPredikt-HRD Assay provides these benefits to Pharma Development Teams:

  • Confidence -
    High Sensitivity and Specificity for HRD Status
  • Easy -
    Utilizes the existing H&E slide or the Tissue Block, no additional samples needed
  • Enroll Patients Sooner -
    Rapid Turn Around Time
  • Cost Savings -
    Up to 80% more cost-effective than NGS methods freeing research funds

“Our team of scientists and engineers have developed a uniquely impactful solution and are very excited to partner with the team at Genetics Institute of America in bringing OncoPredikt HRD to market.”

Mohan Uttarwar, Co-founder and CEO of OneCellDx

Why HRD?

Homologous Recombination Deficiency (HRD) generally occurs when genes involved in the HRR pathway are altered or disrupted and the cells are unable to carry out DNA repair. In tumor cells where backup DNA repair mechanisms are impaired, PARP inhibitors can be used to inhibit action of PARP enzymes which mediate DNA repair of tumor cells making HRD an important biomarker to identify patients who may benefit from PARPi therapy.
AI-enabled prediction of HRD status can be accurately performed on diagnostic H&E slides potentially yielding results quickly and affordably, even when limited tissue is available for testing, thus, providing a reliable and accurate tool to classify HRD status.

NGS Methods

  • 2-4 Weeks Turnaround Time
  • High Failure Rate
  • Significant Tissue Needed
  • Sample QC Rejection for DNA Quality
  • Multi-Technique

OncoPredikt-HRD Assay

  • 2-3 Days
  • Low Failure Rate
  • H&E Stained Slide/FFPE Block
  • High Success Rate
  • One Single Assay

Add the Power of the OncoPredikt-HRD AI Enabled Assay to your PARPi Pharma Development Toolbox

Contact Genetics Institute of America Business Development at:

Email: [email protected]
Phone: 833-443-6522

[1] Offered in USA by GIA under a MOU Commercialization Agreement with OneCell Diagnostics, Cupertino, CA
[2] AI-enabled identification prediction of homologous recombination deficiency (HRD) from histopathology images. Gowhar Shafi, Shivamurthy P.M., Anand Ulle, Krithika Srinivasan, Aravindan Vasudevan, Vikas Jadhav, Dr Sujit Joshi, Nirmal Vivek Raut, Jayant Khandare, Mohan Uttarwar, and Kenneth Joel Bloom
Journal of Clinical Oncology 2022 40:16_suppl, 3019-3019
OncoPredikt HRD Accuracy

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