The Science

Predictive Precision Proteomics is the future

The underlying basis of cancer is genomic alterations which inevitably result in dysregulated protein activity that drives the disease. Accordingly, while a powerful tool to uncover underlying mechanisms of disease, the utility of genomics for patient selection is limited when it comes to drug-response prediction in oncology. Genomic biomarkers have only proven useful for patient selection in the small subset of cancers (~5%) caused by single gene alterations or simple synthetic lethal context. However, the vast majority of cancers contain multiple, complex genomic alterations resulting in the dysregulated tumor-driving protein activity.

Proteomic biomarkers enable direct measurement of disease-driving mechanisms independent of target gene alterations, and allows for accurate matching with the drug mechanism of action.

Acrivon’s Predictive Precision Proteomics (AP3) platform takes proteomics one step further. Our transformative method is widely applicable allowing us to deliver impactful therapies to precisely the right patients.

Acrivon’s Predictive Precision Proteomics-A paradigm change in precision drug development

AP3 is a proprietary, streamlined approach to develop patient selection tumor biopsy tests, called OncoSignature® tests, to identify the patients that will benefit from any particular drug. The method is broadly applicable across drugs and we specifically apply it to clinically active as well as high potential oncology assets for which there is no obvious patient selection path through standard companion diagnostic approaches. AP3 is a transformative, efficient method to accurately match the right therapy to the right patient.

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01.

Biomarker Identification

Our method is engineered to be agnostic to the underlying genetic alterations and enables identification and selection of patients based on direct protein measurement of the critical tumor-driving mechanisms that are regulated by and sensitive to the drug. The AP3 approach leverages unbiased differential global phosphoproteomic drug profiling using mass spectrometry, biased tumor cell analyses and quantitative multispectral in situ imaging analysis of patient derived xenografts (PDXs) and intended-use, intact human formalin-fixed paraffin embedded (FFPE) tumor tissue samples and biopsies, to identify and evaluate biomarkers.

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Non-responder Responder
02.

OncoSignature® Test

The output of our biomarker identification workflow is translated into clinically actionable, drug-specific and proprietary OncoSignature® tests. These are low complexity, automated, quantitative protein immunofluorescence (IF) imaging assays validated on and applied to pretreatment tumor biopsies for patient selection as a companion diagnostic (CDx) in clinical trials.

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Patient Responders

We develop drugs that are effective against major, high unmet need cancer types with multiple driver mutations, and where we believe there can be a significant impact for patients. Our proteomics approach uncovers drug sensitivity and allows for accurate patient responder selection, as well as exclusion of those not benefiting from the treatment.

Our science delivers

The AP3 method efficiently produces a number of valuable, clinically actionable deliverables. These will positively impact the patients receiving our medicines as well as future drug development.

AP3
Patient responder identification
Indication finding
Rational drug combinations
Resistance mechanisms
Pharmacodynamic (PD) biomarkers

We enable patient response prediction

By identifying patients who are most likely to respond to treatment, our medicines become more personalized and ultimately more effective.

We identify drug-sensitive cancer types not previously treated

Using AP3, we can uncover additional cancer indications and tumor types where the drug will be effective.

We reveal rational drug combinations

By targeting the identified drug resistance mechanisms we can design rational combination strategies, as well as fine-tune drug dose and scheduling.

We uncover drug resistance mechanisms

Using AP3 drug profiling we learn about specific biomarkers and pathways related to resistance mechanisms.

We identify pharmacodynamic (PD) biomarkers

These markers help us understand biological effects of our drug and inform our decision making, such as establishing doses and dosing regimens to improve future clinical studies.