A Predictive Tool for Antibody Drug Conjugates

The right treatments. The right patients.

Antibody drug conjugates (ADCs) are targeted chemotherapy designed to bring the chemotherapeutic drug to the cancer cells while sparing normal tissue.

ADCs are at the forefront of new anticancer treatment with more than 170 different ADCs evaluated in clinical trials and 12 clinically approved. Despite their success, ADCs have complex toxicity profiles and there is a variability of response among patients. Thus, many patients experience suboptimal treatment with severe side effects and a reduced chance of response. There is a critical need to improve ADC patient stratification and select the right treatment to each patient.

The Problem

Infographic showing ADC treated population outcomes without Rab Diagnostics technology, showing a group of people split into responders and non-responders.

Current practise in ADC patient selection includes identification of the cancer cell surface marker to which the ADC bind. This practise does not take into account that ADCs needs to be taken up into the cell in order to exert their effect. Our work has focused on identifying intracellular proteins that determine ADC response. We have shown that these proteins can be used as predictive biomarkers for ADCs and thereby  refine patient selection and overall response.

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The Solution

Infographic illustrating ADC treated population using Rab Diagnostics technology to select patients that will respond to treatment.

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ADC patient stratification holds profound implications for both cancer treatment and drug development.

Patients

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Improved patient selection for ADC treatments will increase the response rate and spare patients that are unlikely to respond from treatment that is not working.


Pharma Companies

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Enabling the selection of the right patients for clinical ADC trials, with the potential to increase the response rate and reduce costs and risk in ADC development.


Health Care Providers / Payers

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Selecting the right patients has the potential to save significant costs and provide rational use of limited resources.

Finding the right patients

ADCs represent a new era in cancer treatment. However, there is still a pressing need for advanced biomarker insight to optimize patient selection.

Our data show that Rab-GTPases, a protein crucial in endocytosis, impact ADC efficacy in patients. Furthermore, we have demonstrated that quantification of specific Rab-GTPases expression can be used as a predictive biomarker for ADC response. We have developed proprietary tools, models and assays that predict the response of ADCs to support precision medicine in oncology.

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Discovery/Preclinical

• In vitro cell based models

• Histology studies

• Gene (RNA) /Protein (IHC/IF) expression

• Rab-GTPase RUO kit development

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Benefits

• Understand response rate

• Disease/Market strategy

• Decreased risk and costs

• Improved probability of success

Clinical trials

• Rab-GTPases biomarker prevalence

• Translational studies

• Clinical trial patient selection and stratification

• Diagnostic kit development

Benefits

• Understand ADC MoA

• Biomarker identification

• Lead candidate selection

• Informed decisions

Commercial

• Dx/Rx co-launch

• Complementary diagnostics

• Companion diagnostics

Benefits

• Faster market access

• Improved clinical acceptance and adoption

• Differentiation in the market

Text listing benefits of RabGTPase research and ADCs, including expert guidance, leading research, translatable models, clinical collaborations, AI scoring, and custom study design.
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Management Team

Founder and CEO Anette Weyergang

COO Audun Thornes
CTO and Head of Business Development Hans Christian pedersen

Team

Board of Directors

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Scientific Advisory Board

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. Reach out and let’s make an impact.

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