LiMiTeR Trial

Longitudinal Monitoring of Cancer Treatment Response

The Problem

Most drugs don't work for every tumor. And it takes too long to figure that out.

Currently, first line treatment fails for up to two thirds of cancer patients, and it takes up to 6 months to realize. We think there is a better way. The LiMiTeR trial is an ongoing effort to profile cancer liquid biopsies during treatment. Data are used to help us predict how tumors evolve in response to treatment and how we can adapt our treatment strategies for the best patient outcome.

First line chemotherapy fails for 2 out of every 3 patients with certain cancer types.

Targeted therapies and immunotherapies fail for 1 out of every 3 patients.

Scans can be as infrequent as once every 6 months. Patients are left on ineffective therapies, with all the associated side-effects, for too long. 

The Solution

Precision Oncology: personalize treatments to the individual.

We are currently running studies for longitudinal treatment monitoring in the USA, Europe, and Asia. These studies focus on the analysis of circulating cell-free DNA in a patient's blood. LiMiTeR uses these liquid biopsies for the identification of biomarkers of response and early detection of resistance in cancer patients. We also use this data to power our AI algorithm for predicting tumor evolution over time and in response to therapy. This project empowers oncologists to be more confident in treatment decision making and to be proactive rather than reactive when it comes to treatment planning.

CCG deeply profiles a tumor's biology by DNA and RNA sequencing. We use machine learning and big data analytics to understand what this data means for individual clinical response.

CCG integrates genomic information with EMR data to infer suitable clinical trials or FDA approved drugs. We use machine learning to predict which drugs are likely to be effective.

CCG periodically measures treatment response from low-invasive blood draws. We make sure that the medications predicted to work are indeed working on an individual level.