Innovation Milestones

2021 ~ 2025

Expanded IFP profiling methods in CPAS in additional cancers, analyzing 10,000+ patients and achieving high accuracy, sensitivity and specificity.

Completed 3 lung cancer validation studies, achieving a predictive accuracy of ~91% using whole exome data in determining non-responders to immunotherapy treatment.

Clinical validation studies of Lung Cancer Treatment Response in progress for completion Q2 2025

Created world's only Scientific Reference Database linking deaminase science to molecular and clinical outcomes

Patents

Total 13 patents granted (aggregate total = 31)

First Predicting Efficacy of Cancer Therapy patent granted (Japan 2023)

First Cancer Recurrence Patent granted (Japan 2021)

2016 ~ 2020

First to identify novel Cancer Progression-Associated Signatures (CPAS) across a range of cancers.

First to use deaminase-associated mutations for predicting patient response to immuno-oncology therapies.

Healthy Population Clinical Trial (Monash Clinical Trial Precinct).

First to show that inherited human SNPs are likely caused by mutagenic deaminase activity.

First to use blood DNA to develop an Innate Fitness Score (IFP) for stratifying patients with diseases.

Proof of Concept completed predicting IO responders using >14 datasets across 5 therapies and cancers.

Patents

Total 18 patents granted

First USA patent granted (2020) (Methods for determining the cause of somatic mutagenesis - TSM).

First China patent granted (2020) TSM

First Hong Kong patent granted (2019) TSM

First Australia patent granted (2019) TSM

First Europe patent granted (2018) TSM

First Japan patent granted (2018) TSM

2011 ~ 2015

Initiated basic research to identify deaminase signatures.

First to show that strand-biased mutation patterns seen in immune genes are the same as in many cancers.

First to show that AID/APOBEC and ADAR deaminase- associated mutations occur in protein reading– frame context.

First patent application (Federal Government Innovation Support Grant).

First platform built to automate genomic analysis.

First to identify novel Cancer-Progression Associated Signatures (CPAS) in ovarian cancer.