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Prediction method for synergistic drug combination

A drug and combination technology, applied in the direction of drugs or prescriptions, drug reference, bioinformatics, etc., can solve problems such as difficulties

Pending Publication Date: 2022-05-27
GENOMICARE BIOTECH SHANGHAI CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Due to the large number of existing drugs, the complex (often unknown) mechanisms by which they treat disease, and the complex drug-drug interactions, finding a good drug combination with improved efficacy, toxicity, and other properties of the drug combination can be a challenge extremely difficult

Method used

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  • Prediction method for synergistic drug combination
  • Prediction method for synergistic drug combination
  • Prediction method for synergistic drug combination

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] Example 1. Synergistic Combination of Lenvatinib and PD-1 / PD-L1 Immune Checkpoint Inhibitors in the Treatment of Liver Cancer (Hepatocellular Carcinoma) and Intrahepatic Cholangiocarcinoma (Intrahepatic Cholangiocarcinoma)

[0060] Figure 7 Shown are real survival data of PD-1 / PD-L1 inhibitor combined with lenvatinib in 105 Chinese patients with hepatocellular carcinoma and intrahepatic cholangiocarcinoma, and the evaluation of the ECPH model-based method involved in the present invention. Survival curves in blue (top) are for 46 patients receiving lenvatinib and PD-1 / PD-L1 inhibitor, while survival curves in orange (bottom) are for 59 patients who received PD-1 / PD-L1 inhibition only group of patients treated with the drug. Lenvatinib was a statistically independent good prognostic factor in hepatocellular carcinoma and intrahepatic cholangiocarcinoma following PD-1 / PD-L1 inhibitor therapy. Survival in the combined patient group (lenvatinib and PD-1 / PD-L1) was statis...

Embodiment 2

[0118] Example 2. Combination of resistance (drug resistance) with HLA biomarkers of PD-1 / PD-L1 immune checkpoint inhibitors.

[0119] In this example, a specific HLA-B biomarker was considered as a second factor, which was assessed in a similar manner to that outlined above for combination therapy with PD-1 / PD-L1 drugs. For example, a 2×2 contingency table can be built:

[0120]

[0121] Figure 8Shows true survival data using PD-1 / PD-L1 inhibitors in 445 Chinese patients with hepatocellular carcinoma, cholangiocarcinoma, glioma, lung adenocarcinoma, and soft tissue sarcoma with HLA-B*15:01 factor, and Evaluation data for the ECPH model-based method of the present invention. Survival curves in blue (bottom) are the patient group of 47 HLA-B*15:01 plus PD-1 / PD-L1 inhibitors, while orange (top) curves are 398 HLA-B*15:01 without There was a patient group that added PD-1 / PD-L1 inhibitors. HLA-B*15:01 was a statistically independent major poor prognostic factor in solid tu...

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Abstract

A method of using a computer to determine the effect of drug combination on the outcome of a treatment. A plurality of genomic and clinical variables may be generated from genomic data, EHR data, and clinical treatment data. The first drug and the second drug (or biomarker) are combined, and an independent risk factor, an accumulated risk ratio and a P value are calculated based on a Cox proportional risk model, so that the action property of the combination of the first drug and the second drug (or biomarker) on disease treatment is determined.

Description

Background technique [0001] Drug combinations are widely used to treat diseases, including some of the most dreaded diseases, such as cancer and AIDS. Often, drug combinations have better therapeutic effects than single anticancer drug treatments. The principles of drug combination include improving therapeutic effect, reducing dose and toxicity, and reducing or delaying drug resistance. [0002] Due to the large number of existing drugs, the complex (often unknown) mechanisms by which they treat disease, and the complex drug-drug interactions, finding a good drug combination with improved efficacy, toxicity, and other properties of the drug combination may be extremely difficult. Experimental screening of possible drug combinations is not feasible due to limited resources. [0003] There is a need to develop better reliability / accuracy prediction methods for drug combination properties. SUMMARY OF THE INVENTION [0004] The present invention provides computer-implemente...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H70/40G06F16/2457
CPCG16H50/70G16B20/00G16H20/10G16H50/30
Inventor 许强王冠张翼毋冰
Owner GENOMICARE BIOTECH SHANGHAI CO LTD
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