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68 results about "Approved drug" patented technology

An approved drug is a preparation that has been validated for a therapeutic use by a ruling authority of a government. This process is specific by country.

Compositions & formulations for preventing and treating chronic diseases that cluster in patients such as cardiovascular disease, diabetes, obesity, polycystic ovary syndrome, hyperlipidemia and hypertension, as well as for preventing and treating other diseases and conditions

Patients inflicted with various clustering chronic diseases require treatment with multiple drugs having distinct mechanisms of action. Accordingly, patients with multiple conditions suffer from cumulative side effects of multiple drugs as well as drug-drug interactions. Embodiments, agents, compounds or drugs of the present invention, such as sesquiterpenes, e.g., Zerumbone, replace an equal or larger number of approved drugs during patient treatment. Examples of disorders prevented or ameliorated by administration of the formulations of this invention include but are not limited to inflammatory diseases that may be, oncological, genetic, ischemic, infectious, neurological, hematological, ophthalmological, rheumatoid, orthopedic, neurological, hematological, kidney, vascular, dermatological, gynecological, or obstetric. The present invention further relates to a method of identifying agents, compounds or drugs useful in preventing or treating CDCP related diseases and conditions as well as other disorders, diseases and conditions treatable or preventable by the same agents, compounds or drugs.
Owner:REID CHRISTOPHER BRIAN

Drug recommendation algorithm based on depth learning

InactiveCN107092797AEfficient Online Drug PurchaseSolve the problem of lack of expert guidance on drug purchaseMedical automated diagnosisBuying/selling/leasing transactionsDiseasePersonalization
The present invention provides a drug recommendation algorithm based on depth learning. The present invention belongs to the field of computer software. a model of correspondence between drug effects and diseases is constructed in a framework of depth learning, and based on the mode, a personalized drug recommendation algorithm is proposed. The recommendation algorithm provided by the present invention comprises three parts: first, a drug-related information acquisition process, which comprises acquiring a name of an approved drug as well as a disease treated thereby, a side effect of the drug, precautions for use and other information from CFDA, and acquiring information such as sales data, user comments and price of the drug from an online drug mall; next, a depth learning feature training process, which comprises construction of a training network based on depth learning, a feature parameter training process, and output of drug classification information; and finally, individual recommendation, which comprises drug recommendation based on long-term personal health features and an implementation process thereof. The algorithm provided by the present invention better solves the problem that users lack instructions on drug purchasing from experts.
Owner:广东亿荣电子商务有限公司 +1

Ligands that target hepatitis c virus e2 protein

Hepatitis C Virus (HCV) infects 200 million individuals worldwide. Although several FDA approved drugs targeting the HCV serine protease and polymerase have shown promising results, there is a need for better drugs that are effective in treating a broader range of HCV genotypes and subtypes without being used in combination with interferon and/or ribavirin. Recently, the crystal structure of the core of the HCV E2 protein (E2c) has been determined, providing structural information that can now be used to target the E2 protein and develop drugs that disrupt the early stages of HCV infection by blocking E2's interaction with different host factors. By targeting sites containing conserved E2 amino acids in the CD81 binding site on HCV E2, one might also be able to develop drugs that block HCV infection in a genotype-independent manner. Using the E2c structure as a template, a structural model of the E2 protein core (residues 421-645) was developed that includes the three amino acid segments that are not present in the E2c crystal structure. Blind docking of a diverse library of 1715 small molecules to this model led to the identification of a set of 34 ligands predicted to bind near conserved amino acid residues involved in the HCV E2:CD81 interaction. Surface plasmon resonance was used to screen the ligand set for binding to recombinant E2 protein, and the best binders were subsequently tested to identify compounds that inhibit the infection of hepatocytes by HCV. One compound, 281816, blocked E2 binding to CD81 and inhibited hepatocyte infection by HCV genotypes 1a, 1b, 2a, 2b, 4a and 6a with IC50's ranging from 2.2 μM to 4.6 μM. Methods are described for preventing or treating HCV infection using small molecule inhibitors such as 281816 that target E2 and disrupt its interactions.
Owner:AMERICAN UNIV OF CAIRO
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