Biodesix has been granted a patent for a method that predicts whether a melanoma patient will benefit from high dose IL2 therapy. The method involves using mass spectrometry data from a blood sample and a computer classifier developed from a reference set of mass spectral data. The classifier can also be used in combination with data from patients treated with an anti-PD-1 immunotherapy drug to guide treatment decisions. GlobalData’s report on Biodesix gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on Biodesix, AI-assisted drug screening was a key innovation area identified from patents. Biodesix's grant share as of September 2023 was 41%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting benefit of high dose il2 therapy for melanoma patients
A recently granted patent (Publication Number: US11710539B2) describes a method for predicting the effectiveness of high dose IL2 therapy in melanoma patients. The method involves several steps, including performing mass spectrometry on a blood-based sample from the patient and obtaining mass spectrometry data. A computer then uses a classifier developed from a set of samples from melanoma patients treated with high dose IL2 therapy to classify the mass spectrometry data. The classifier is implemented as a hierarchical combination of two classifiers, with the first classifier classifying the patient into an Early or Late group, and the second classifier further classifying the Late group into a second Early or Late group. The patient's classification into the Late group or second Late group indicates a likelihood of benefiting from high dose IL2 therapy. The method also involves determining a Late class label for the sample and administering the high dose IL2 therapy based on this label.
Additionally, the patent claims methods for detecting class labels for melanoma patients and detecting class labels for melanoma patients on high dose IL2 therapy. These methods involve performing mass spectrometry on blood-based samples and using a classifier developed from a set of samples obtained from melanoma patients treated with an anti-PD-1 drug. The classifier is used to generate class labels, which can indicate the likelihood of benefiting from the anti-PD-1 drug. The class labels are determined based on the mass spectrometry data and can be used to guide treatment decisions.
Overall, this patent describes a method for predicting the effectiveness of high dose IL2 therapy in melanoma patients using mass spectrometry data and a hierarchical combination of classifiers. The method has potential applications in personalized medicine, allowing for more targeted and effective treatment decisions for melanoma patients. Additionally, the patent claims methods for detecting class labels for melanoma patients, which can be useful in guiding treatment decisions for patients on anti-PD-1 therapy.