A Clinical Trial Simulation and Disease Prediction System Based on Digital Twin Technology

Abstract

This invention provides a clinical trial simulation and disease prediction system based on digital twin technology, comprising: an input module having a gene sequence database, a molecular and omics database, a metabolic and endocrine database, an organ and system database, an environmental exposure database, a personality trait database, a dietary intervention database, a drug intervention database, and a developmental pathway database; and a digital bionic module having a processing unit and electrically connected to a physiological parameter and endocrine search unit, a psychological behavior and environmental search unit, a molecular and epigenetic search unit, a modeling compensation unit, and a twin modeling generation unit. The processing unit executes its stored artificial intelligence program to cause the twin modeling generation unit to generate a digital twin unit corresponding to the test subject, which is then provided to medical personnel for relevant testing and to obtain corresponding treatment plans.

Claims

1. A clinical trial simulation and disease prediction system based on digital twin technology, comprising: an input module, which includes a gene sequence database, a molecular and omics database, a metabolic and endocrine database, an organ and system database, an environmental exposure database, a personality trait database, a dietary intervention database, a drug intervention database, and a developmental pathway database for storing and transmitting required data, wherein... The gene sequence database stores multiple gene sequence data; and a digital bionic module includes a processing unit and electrically connected to the processing unit a physiological parameter and endocrine search unit, a psychological behavior and environment search unit, a molecular and epigenetic search unit, a modeling compensation unit, and a twin modeling generation unit. The processing unit is electrically connected to the input module, and executes its stored artificial intelligence program to transmit and process the data from the input module to generate a digital twin unit. The processing unit executes its stored artificial intelligence program to cause the twin modeling generation unit to generate the corresponding digital twin unit for the test subject based on the physiological parameter and endocrine search unit, the psychological behavior and environment search unit, the molecular and epigenetic search unit, and the modeling compensation unit.

2. As described in claim 1, a clinical trial simulation and disease prediction system based on digital twin technology, further comprising an electrically connected simulation prediction module for data transmission and computation, wherein the simulation prediction module includes a gene regulation simulation unit, a pharmacokinetics simulation unit, and a psychophysiological interaction simulation unit, wherein... The gene regulation simulation unit simulates the linkage at the microscopic molecular level based on the gene sequence data; the pharmacokinetic simulation unit simulates the metabolic state of the drug's compounds in different organs; and the psychophysiological interaction simulation unit is used to simulate the effects of physiological changes on emotions and cognition.

3. As described in claim 1, a clinical trial simulation and disease prediction system based on digital twin technology, further comprising an electrically connected specific simulation prediction module for data transmission and computation, wherein the specific simulation prediction module includes a cardiovascular system prediction unit, a respiratory system prediction unit, and a digestive system prediction unit, wherein the cardiovascular system prediction unit simulates cardiovascular circulatory dynamics based on a GATA4 gene stored in the gene sequence database, the respiratory system prediction unit simulates lung function based on an SFTPB gene stored in the gene sequence database, and the digestive system prediction unit simulates metabolic pathways based on an HNF4A gene stored in the gene sequence database.

4. As described in claim 3, a clinical trial simulation and disease prediction system based on digital twin technology, further comprising a skeletal system prediction unit, a muscular system prediction unit, and a nervous system prediction unit, wherein the skeletal system prediction unit simulates bone density based on a RUNX2 gene stored in the gene sequence database, the muscular system prediction unit simulates muscle mass and metabolism based on a MYOD1 gene stored in the gene sequence database, and the nervous system prediction unit simulates cognition and neurodegeneration based on a PAX6 gene stored in the gene sequence database.

5. A clinical trial simulation and disease prediction system based on digital twin technology as described in claim 3, further comprising an endocrine system prediction unit and an immune and lymphatic system prediction unit, wherein the endocrine system prediction unit simulates hormone levels based on a POU1F1 gene stored in the gene sequence database, and the immune and lymphatic system prediction unit simulates immune defense based on a RAG1 gene stored in the gene sequence database.

6. A clinical trial simulation and disease prediction system based on digital twin technology as described in claim 3, further comprising a urinary system prediction unit, a reproductive system prediction unit, and an epidermal system prediction unit, wherein the urinary system prediction unit simulates kidney filtration efficiency based on one of the / WT1 genes stored in the gene sequence database, the reproductive system prediction unit simulates reproductive health based on one of the SRY / WNT4 genes stored in the gene sequence database, and the epidermal system prediction unit simulates skin barrier and aging based on one of the KRT1 genes stored in the gene sequence database.

7. A clinical trial simulation and disease prediction system based on digital twin technology as described in claim 1, further comprising the gene sequence data stored in the gene sequence database including at least one GATA4 gene, one SFTPB gene, one HNF4A gene, one RUNX2 gene, one MYOD1 gene, one PAX6 gene, one POU1F1 gene, one RAG1 gene, one WT1 gene, one SRY / WNT4 gene, one KRT1 gene, one OCT4 gene, one SOX2 gene, one NANOG gene, one NODAL gene, one BMP4 gene, one HOXA gene, one SHH gene, one TBX5 gene, one NOTCH1 gene, one VRGFA gene, one ASCL1 gene, one EPO gene, one GH1 gene, one IGF1 gene, one FOXP3 gene, one TP53 gene, one CDKN2A(P16) gene, one TERT gene, and one MTOR gene.

8. A clinical trial simulation and disease prediction system based on digital twin technology as described in claim 1, further comprising a developmental pathway database storing multiple biological logical data, each of which includes an early embryonic process, an organogenesis basal period process, a fetal developmental period process, an infancy process, and an adult process, wherein, The early embryonic development process is associated with the genes OCT4, SOX2, NANOG, NODAL, and BMP4; the basal organogenesis process is associated with the genes HOXA, SHH, PAX6, TBX5, and NOTCH1; the fetal development process is associated with the genes VEGFA, ASCL1, GATA4, SFTPB, and EPO; the infancy process is associated with the genes GH1, IGF1, RUNX2, RAG1, and FOXP3; and the adult development process is associated with the genes TP53, CDKN2A (p16), TERT, MTOR, and SIRT1.

9. A clinical trial simulation and disease prediction system based on digital twin technology as described in claim 1, further comprising: a molecular and omics database storing multiple single nucleotide polymorphism data, multiple DNA methylation data, multiple proteomic data, and multiple gut microbiota data; a metabolic and endocrine database storing multiple blood glucose data, multiple blood lipid data, multiple cortisol data, multiple sex hormone data, and multiple inflammatory marker data; an organ and system database storing multiple heart rate variability data, multiple blood oxygen data, multiple vital capacity data, multiple bone mineral density data, and multiple arteriosclerosis degree data; and an environmental exposure database storing multiple air quality data, multiple noise level data, multiple ultraviolet radiation exposure data, and multiple heavy metal residue data.

10. A clinical trial simulation and disease prediction system based on digital twin technology as described in claim 1, further comprising: a personality trait database storing multiple personality trait data, multiple cognitive function data, multiple emotional state data, multiple stress and neural response data, and multiple social trajectory data; a dietary intervention database storing multiple eating behavior data and multiple addiction and preference data; and a drug intervention database storing multiple drug intervention parameter data.

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