sujant

DeepPurpose

A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)

chembl_webresource_client

Official Python client for accessing ChEMBL API

Med-BERT

Med-BERT, contextualized embedding model for structured EHR data

admiral

ADaM in R Asset Library

awesome-drug-pair-scoring

Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)

CDISC_pilot_replication

A modern replication of the CDISC pilot table outputs, using the PHUSE Test Data Factory ADaM data, using the R programming language

cdisc-rules-engine

Open source offering of the cdisc rules engine

ADRtarget

Machine learning guided association of adverse drug reactions with in vitro off-target pharmacology

pvm

A collection of signal detection methods used in the field of pharmacovigilance

Predicting-Adverse-Drug-Reactions-with-Machine-Learning

The objective of this work is to develop machine learning (ML) methods that can accurately predict adverse drug reactions (ADRs) using the databases SIDER and OFFSIDES.

An-Attentive-Neural-Model-for-labeling-Adverse-Drug-Reactions

An Attentive Neural Sequence Labeling Model for Adverse Drug Reactions Mentions Extraction

openfda-faers

FAERS Adverse Reaction Events database and OpenFDA API

vigipy

A medical device/pharmacovigilance library written in python

InternetArchive-Pharmacovigilance-Tweets

This repository contains the code of Mining archive.org’s Twitter stream grab for Pharmacovigilance research gold paper.

BERT-Social-Media-Pharmacovigilance

An Honors Thesis on sentiment analysis of tweets mentioning drug affects.

APRILE

APRILE: A python library for exploring Adverse Polypharmacy Reaction using Intelligent Learner and Explainer

openfda-bigdata-pipeline

OpenFDA BigData Pipeline

Extraction-of-Adverse-Drug-Reaction-from-Unstructured-Data-using-Bidirectional-LSTM-Network

For this problem, we proposed the use of bidirectional-LSTM’s(Long Short Term Memory) with 1-D CNN layer to classify patient notes at character level and at word level. The 1-D CNN is employed to scale back the training time. In order to improve the performance, we will also feed the network combined word embedding consisting of Pre-trained word2vec 100 dimension word embedding trained on the Twitter ADR Dataset database and character embedding generated by a Char-CNN for Named Entity Recognition

LP-SDA

Code and Datasets for the paper "Towards early detection of adverse drug reactions: combining pre-clinical drug structures and post-market safety reports", published on BMC Medical Informatics and Decision Making in 2019.

EMADB-Autopilot

Automated browser to download drug adverse reaction reports from the European Database of Suspected Adverse Reactions Reports (EudraVigilance)

Admiral-Hackathon

Code for the CDISC {admiral} hackathon, Feb 2023. The objective of this hackathon is to develop ADaM datasets in R using the ADaM in R Asset Library {admiral} and other Pharmaverse packages.

HITBert

A fine-tuned BERT-based NLP model for classyfing HIT-related adverse events reports

mimic_ade_prediction

Prediction of adverse drug events using the MIMIC-IV and MIMIC-IV-ED datasets

Designated-Medical-Event-Pathways

This is a repository of pathways discovered using PathFX to better understand drug-induced designated medical events listed in warnings, boxed warnings, and precautions on drug labels.

AdverseDrugEventPipeline

Drug Side Effect Checker - The Pharmacovigilance Dashboard Prototype build with FDA (FAERS) data

ADR-detection-BioBERT

The repo consists of an ML model based on BioBERT by virtue of transfer learning, to detect adverse drug reactions (ADRs). It also consists of the data used by the model.

study_design_diagram

This is the package for drawing study design workflow diagrams by inputting TA dataset of SDTM from CDISC standard

MAITAI

AbbVie-Adverse-Drug-Prediction

Create a model that can predict likelihood of all adverse events for ALL drug pair combinations. The two relevant datasets (FAERS and Chemble) will be merged and used to predict likelihood of adverse effects.

ClinicalTrial

Prediction of the occurrence of adverse events during clinical trials from the drug feature