Industry Insights - Pharma & Life Sciences
With the advance of AI and machine learning, high-quality and transparent data now has the power to accelerate the development of predictive models. ...
The use of FAIR (Findable, Accessible, Interoperable and Reusable) data in drug discovery and development could be transformational. ...
Although Artificial Intelligence (AI) is nothing new, applying AI techniques to small-molecule drug discovery started to become feasible just the past couple years. ...
5 key steps to improve literature screening workflows for safety signal detection can positively impact the whole life cycle of a drug. ...
ErbB1 kinase is the cell-surface receptor for epidermal growth factor. Its dysfunction has been implicated in diseases such as cancer. ...
Effective drug discovery depends on a deep understanding of the function and therapeutic potential of a compound. ...
The first marketed selective T-type calcium channel blocker mibefradil was withdrawn due to adverse drug interactions. ...
Most traditional drugs act on more than one target, exhibiting a complex, multifaceted pharmacological profile. ...
In silico techniques require exhaustive data and sophisticated, well-structured informatics tools to help scientists gain insights of compound behavior. ...
Sweet Spot of a Killer - Industry insights - Pharma and life sciences ...
Translational medicine is a powerful concept that has had an evolving definition. ...
Cancer immunotherapy shows considerable promise as an effective treatment, especially for cytotoxic-resistant cancers such as melanoma. ...
Spontaneous reports of adverse events are a core source of information. They offer a unique, unrestricted perspective on drug performance. ...
Cancer is often viewed as one monolithic disease, but every cancer is unique. Therapies with accurate diagnosis are needed to effectively fight the disease ...
Biases and heterogeneity in the data of spontaneous adverse event reporting systems can make it hard to gain the insights to inform decisions. ...
