This webinar will present a case study demonstrating how chemotherapy exposure measurement via patient-centric sampling can drive personalized, more effective, and safer cancer treatments.
Chemotherapy dosages are often prescribed based on body surface area (BSA), an outdated method that doesn’t consider individual differences in drug metabolism. This can lead to underdosing or overdosing, reducing treatment efficacy or causing toxic side effects. In this presentation, we will introduce True Dose’s patented technology, designed to measure precise drug levels through patient-centric self-sampling. We’ll discuss how this approach personalizes treatment, linking drug exposure to side effects, and leveraging both venous and capillary blood samples via mobile phlebotomy. Our goal is to revolutionize diagnostics in chemotherapy to increase precision and improve patient outcomes.
Ideal for:
Clinical researchers and trial designers seeking to improve precision medicine in cancer treatment.
Oncologists and healthcare providers aiming to offer personalized chemotherapy dosing.
Clinical trial professionals focused on patient recruitment, retention, and improving trial participation rates.
Developers of medical devices and diagnostic tools who are interested in integrating patient-centric sampling methods.
Pharmacologists and geneticists exploring drug metabolism and the role of pharmacogenomics in tailoring treatments.
What you will learn
How True Dose’s at-home sampling technology is transforming precision medicine and improving chemotherapy dosing accuracy.
The limitations of body surface area (BSA) dosing and how personalized drug exposure measurement can solve this challenge.
A case study on linking chemotherapy dose concentrations with patient side effects using patient-centric blood sampling.
The benefits and obstacles of incorporating mobile phlebotomy and self-sampling techniques in clinical trials.
How integrating True Dose technology reduces patient burden, increases participation, and delivers personalized treatment based on metabolic and genetic factors.
