What does the ImpriMed Personalized Prediction Profile include?

The Personalized Prediction Profile includes our Immunoprofile report and anticancer drug response predictions generated by artificial intelligence models. The predictions include estimates of both (1) the likelihood of a positive clinical response (partial response/ complete remission) to individual anticancer drugs and (2) the likelihood complete remission after 1 or 2 cycles of CHOP therapy, and the likelihood of early relapse after a successful CHOP regimen.Outcome predictions are currently provided for 13 individual drugs that are commonly used in many first-line and rescue protocols for the treatment of canine lymphoma (including CHOP, LOPP, MOPP, LPP, Tavonea only, etc…).Predictions are included for Doxorubicin, Cyclophosphamide, Vincristine, Vinblastine, Prednisone, Rabacfosadine (Tanovea®), L-Asparaginase, Lomustine, Mitoxantrone, Mechlorethamine, Dexamethasone, Chlorambucil, and Melphalan.

Other Questions

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How much blood is required for Personalized Prediction Profile for Canine Lymphoma?

We require at least 2mL of whole blood sample in an EDTA-treated tube.

Does pet insurance cover ImpriMed?

Most pet insurance plans that cover cancer care will typically cover ImpriMed’s services. Please check with your insurance representative to see if your plan can cover the services.

How do vets report back the outcomes to feed back into the AI model? Is this something that can be easily done via the Vet portal?

We usually send you an email asking for patient records about 3-6 months after you receive the final ImpriMed report. Once we receive the record, we input the data into the AI Models, it is not yet something that can be submitted on the Vet Portal.

Which cancers can I use ImpriMed for? or What type of cancer does ImpriMed predict?

Currently, our services are for canine lymphoma and leukemia. We will be expanding our services to other species and other blood / lymphoid cancers in the near future.

How does ImpriMed predict drug responses?

Our predictions are made by artificial intelligence (AI) models trained to predict clinical outcomes from patient data inputs. Clinical outcomes collected from oncologists include reports of progressive disease, stable disease, partial response, and complete response. Patient data used as inputs by the AI models include readings from our live-cell drug sensitivity assay, flow cytometry, PARR, and patient information.Models are re-trained periodically to incorporate new data and refine performance.