Implementation of Machine Learning in Drug Development
Significant recent investment in computational technology has seen a number of new innovations arise in drug discovery - perhaps most notable machine learning (ML). By 2022, it is expected that AI technology will contribute $2.199 billion to pharma’s revenue, with...
4 years agoImplementation of Machine Learning in Drug Development
Significant recent investment in computational technology has seen a number of new innovations arise in drug discovery - perhaps most notable machine learning (ML). By 2022, it is expected that AI technology will contribute $2.199 billion to pharma’s revenue, with...
4 years ago
-SAVED-Optimising The Manufacturing Process of Drug Development to Meet Demand
Over the last decade, biopharmaceutical manufacturing has needed to evolve rapidly to keep up with clinical demand for products. Innovations in recent years have seen production increase output quantities in a shorter period of time. Adaptations to production including single-use...
4 years ago-SAVED-Optimising The Manufacturing Process of Drug Development to Meet Demand
Over the last decade, biopharmaceutical manufacturing has needed to evolve rapidly to keep up with clinical demand for products. Innovations in recent years have seen production increase output quantities in a shorter period of time. Adaptations to production including single-use...
4 years ago
Predicting Drug Toxicity: Challenges and Innovations
Failure to reach the desired safety profile is one of the main reasons for delayed drug development. Advancements in preclinical studies have seen the optimisation of in vitro assays to better predict toxicity in drug discovery. Computational methods like in...
4 years agoPredicting Drug Toxicity: Challenges and Innovations
Failure to reach the desired safety profile is one of the main reasons for delayed drug development. Advancements in preclinical studies have seen the optimisation of in vitro assays to better predict toxicity in drug discovery. Computational methods like in...
4 years ago
Real World Data and Evidence: Emerging Trends Across Clinical Research
Real-world data (RWD) and real-word evidence (RWE) are increasingly used to support drug development and clinical research across life sciences. RWE studies provide insight into the implementation of therapeutic drugs clinical practice based on RWD of the patient population. RWD...
4 years agoReal World Data and Evidence: Emerging Trends Across Clinical Research
Real-world data (RWD) and real-word evidence (RWE) are increasingly used to support drug development and clinical research across life sciences. RWE studies provide insight into the implementation of therapeutic drugs clinical practice based on RWD of the patient population. RWD...
4 years ago
Strategies to Optimise Companion Diagnostics in Cancer
Companion diagnostic tests are an important part of precision medicine in oncology. In addition to matching optimal treatment options for patients, these tests enable clinicians to monitor the efficacy of therapeutic intervention in disease management. Innovations in cancer biopsies and...
4 years agoStrategies to Optimise Companion Diagnostics in Cancer
Companion diagnostic tests are an important part of precision medicine in oncology. In addition to matching optimal treatment options for patients, these tests enable clinicians to monitor the efficacy of therapeutic intervention in disease management. Innovations in cancer biopsies and...
4 years ago
Phenotypic Screening in Early Drug Discovery: Opportunities and Challenges
Despite the prevalence of target-based discovery, phenotypic screening is emerging as a popular technique in early drug discovery. Challenges with target-based delivery have shown obvious flaws with predictive validity. The latest application of AI in phenotypic drug discovery has shown...
4 years agoPhenotypic Screening in Early Drug Discovery: Opportunities and Challenges
Despite the prevalence of target-based discovery, phenotypic screening is emerging as a popular technique in early drug discovery. Challenges with target-based delivery have shown obvious flaws with predictive validity. The latest application of AI in phenotypic drug discovery has shown...
4 years agoInterested?
Reserve your space
