Personal SPECT: A Wearable Sensor Array for Continuous Real-Time Dosimetry for Theranostics
Abstract
The goal of this project is to create a wearable, at home, SPECT capable of continuous dosimetry monitoring to tumors and organs at risk (OARs) after targeted radionuclide therapy (TRT) for prostate cancer. This will solve a major unmet need to optimize the TRT dose for each patient based on their unique and widely varying biodistribution and tumor uptake and retention profiles – moving away from the current one size fits all dosing approach to a personalized method maximizing the dose to the tumor, while not causing toxicity. Despite a swell of new drug approvals over the past 10 years for the treatment of metastatic castration-resistant prostate cancer (mCRPC), these therapies are not truly curative. Thus, developing new strategies to ablate mCRPC is an urgent unmet need. Radiotherapy is an effective and promising treatment for prostate cancer – in part due to its simplicity; delivery of high doses to the tumor will ablate it, but the challenge resides in delivering that dose safely without exceeding the dose to surrounding critical organs. Unfortunately, standard (external beam) radiotherapy cannot be targeted to many areas in the body at the same time, precluding treatment for mCRPC. However, radioligand therapy, in which a radioactive drug is administered systemically and carries radiation to all tumors within the body simultaneously, is a treatment strategy that has been used for decades to cure deadly tumors like thyroid cancer. Recently, promising clinical trial results have emerged for the use of TRT targeting prostate-specific membrane antigen (PSMA) on mCRPC cells. That said, many patients experience no benefit or recur quickly. This is due primarily to the inadequate dose delivered to the tumor, driven by using a one-size-fits-all approach that is based on data models that do not consider the biological variability between tumors that we know to exist among mCRPC patients. Thus, the administration of the radioligand therapy is in no way personalized to the patient. On this basis, we hypothesize that monitoring dose distribution continuously will enable optimization and personalization of TRT – maximizing the therapeutic ratio for each patient. This will be even more important as alpha radionuclides (300X more powerful than 177Lu) and synergistic TRT-drug combinations are introduced into clinical trials, such as with DNA damage response agents or immunotherapy drugs. Currently, it is not possible to monitor in real time how much radioligand is depositing within tumors, and the field is therefore blind to drug-tumor interactions and simply must wait weeks to months for evidence to tumor responses. Developing new technologies to study the interaction between tumors and radioligand therapy continuous and in real time is a major unmet need that we aim to address during this project. Real-time, ultrasensitive dosimetry remains an important, yet elusive, goal due to the inherent physical properties of radioactive particles; long half-lives (~7 days) require continuous monitoring to obtain accurate dosimetry, and the current state of the art (SPECT imaging) is not available at all centers and cannot feasibly be done on a repeated basis. We solve this problem by introducing a wearable, at home, SPECT dosimetry platform enabled by millimeter-scale nano-electronic dosimetry chips that will enable us to measure radiation in both tumors and normal tissues remotely. In this proposal, we build on our validated prototype capable of detecting gamma emissions from 177Lu, by making it more sensitive, embedding it in a wearable array, and using an algorithm that takes data from a PSMA-PET to allow reconstruction of all dosimetry from a few strategically placed wearable sensors. We validate this prototype on a mouse model of prostate cancer, which is readily scalable to a patient, as the chips are made using computer-chip technology (and easily mass fabricated), and, while patient measurements distances are
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310159
Entities
People
- Mekhail Anwar
Organizations
- United States Army
- University of California, San Francisco