34 results about "Drug-drug interaction" patented technology

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.

A processor-implemented method, computer program product and system are provided for predicting drug-drug interactions based on clinical side effects. The method includes constructing a drug-drug interactions training dataset that includes pharmaceutical, pharmacokinetic or pharmacodynamics drug-drug interactions from multiple data sources for each of a plurality of drugs. The method also includes constructing side effect features for each of the drugs from side effects associated with the drugs. The method further includes building, using the drug-drug interactions training dataset, a drug-drug interactions classifier that predicts adverse drug-drug interactions for drug pairs derivable from the drugs. The method additionally includes for each of the side effects, building a two-by-two table using the side effect features, and performing a Fisher's exact test using the two-by-two table to determine whether a given one of side effects is differentially shown between positive predicted drug-drug interactions and negative predicted drug-drug interactions.

A computer system for obtaining, analyzing and providing information to a community of user patients regarding their medication is disclosed. The system is provided by means of world wide web access and generates a user patient screen prompting the manual entry of data relating to the use patient and drugs being taken. The data are analyzed and results are provided to the user patient and / or the caregiver including drug-drug interactions, drug pricing, alternative medications and possible adjustments in the dosing regimen of the user patient.

The present invention relates to a stable solid oral pharmaceutical multi-component composition comprising combination of blood pressure lowering drugs with lipid lowering agent / s and optionally a platelet aggregation inhibitor in a single dosage form. The blood pressure lowering agents are selected from β-adrenergic receptor blocking agent, ACE inhibitor and diuretic. The lipid lowering agent is selected from HMG Co-enzyme-A reductase inhibitor. The pharmaceutical composition made as per present invention a) overcomes any drug-drug interactions, b) exhibits pharmacokinetic and pharmacodynamic profile of individual therapeutic agent, c) has minimal side effects. The invention provides multi-component composition (MCC) to increase adherences to therapy. The MCC as per present invention provides compositions that maintain activity of all active ingredients without significant increase in adverse event profile. The present invention further relates to a method of preparing the said pharmaceutical composition.

The present invention provides a method for constructing a database of atomic fingerprint descriptors. The invention provides a method for predicting activation energy using an atomic fingerprint descriptor and an atomic descriptor, the method comprising the steps of: (i) calculating the atomic fingerprint descriptor of a substrate; (ii) comparing the calculated atomic fingerprint descriptor with the constructed atomic fingerprint descriptor database to select an atomic position where cytochrome P450-mediated metabolism occurs; and (iii) predicting activation energy for the selected atomic position using an atomic descriptor. Also, the invention provides a method of predicting the activation energy of CYP450-mediated phase I metabolism using effective atomic descriptors. Specifically, the invention provides a method of predicting the activation energy either for cytochrome P450-mediated hydrogen abstraction or for tetrahedral intermediate formation in cytochrome P450-aromatic hydroxylation using equations including effective atomic descriptors. The method of the invention can rapidly predict activation energy for phase I metabolites at a practical level without having to perform a docking experiment between any additional CYP450 and the substrate, or a quantum mechanical calculation, thereby making it easier to develop new drugs using a computer. Also, the present invention may propose a strategy for increasing the bioavailability of drugs through the avoidance of metabolites based on the possibility of drug metabolism. Furthermore, the method of the present invention proposes new empirical approaches which can also be easily applied to activation energies for various chemical reactions, and makes it possible to explain physical and chemical factors that determine activation energy. In addition, through the prediction of activation energy according to the present invention, it is possible to predict i) metabolic products, ii) the relative rate of metabolism, iii) metabolic regioselectivity, iv) metabolic inhibition, v) drug-drug interactions, and vi) the toxicity of a metabolite.

Methods are directed at utilizing a patient's electronic medical record (EMR) information accessed from a cloud, such as that used in Blue Button technology. Once the patient's EMR information is downloaded from the cloud, it is used to automatically determine if the patient is eligible to participate in a clinical trial. The EMR information of the patient is also utilized to determine if there is a potential drug-drug interaction from of the one or more medications the patient is prescribed to take. Furthermore, the patient's EMR information is used to identify any warnings and indications regarding the one or more medications the patient is prescribed to take. Notifications are then sent to a patient device and devices of those that have permission from the patient to receive such information, such as family members.