Top 100 bestselling drugs represent an arena struggling for new FDA approvals: drug age as an efficiency indicator

Functional and Material Properties in Nanocatalyst Design: A Data Handling and Sharing Problem

(1) Background: Properties and descriptors are two forms of molecular in silico representations. Properties can be further divided into functional, e.g., catalyst or drug activity, and material, e.g., X-ray crystal data. Millions of real measured functional property records are available for drugs or drug candidates in online databases. In contrast, there is not a single database that registers a real conversion, TON or TOF data for catalysts. All of the data are molecular descriptors or material properties, which are mainly of a calculation origin. (2) Results: Here, we explain the reason for this. We reviewed the data handling and sharing problems in the design and discovery of catalyst candidates particularly, material informatics and catalyst design, structural coding, data collection and validation, infrastructure for catalyst design and the online databases for catalyst design. (3) Conclusions: Material design requires a property prediction step. This can only be achieved based on the registered real property measurement. In reality, in catalyst design and discovery, we can observe either a severe functional property deficit or even property famine.

Ligand potency - an essential estimator for drug design: between intuition, misinterpretation and serendipity

This is a review of developments in the field of potency, which is an essential estimator for drug design. We discuss the basic concepts of research and discovery, focusing on how misinterpretation in this area, - but also intuition and serendipity, which are common in drug design - helped us to pave a bumpy road towards better drugs. How far we still are from this goal can be seen in the Eroom law, which states that the efficiency of pharma research and development is decreasing. At the same time, pharma bestsellers are getting older.

The analysis of the market success of FDA approvals by probing top 100 bestselling drugs

Target-oriented drug discovery is the main research paradigm of contemporary drug discovery. In target-oriented approaches, we attempt to maximize in vitro drug potency by finding the optimal fit to the target. This can result in a higher molecular complexity, in particular, the higher molecular weight (MW) of the drugs. However, a comparison of the successful developments of pharmaceuticals with the general trends that can be observed in medicinal chemistry resulted in the conclusion that the so-called molecular obesity is an important reason for the attrition rate of drugs. When analyzing the list of top 100 drug bestsellers versus all of the FDA approvals, we discovered that on average lower-complexity (MW, ADMET score) drugs are winners of the top 100 list in terms of numbers but that, especially, up to some optimal MW value, a higher molecular complexity can pay off with higher incomes. This indicates that slim drugs are doing better but that fat drugs are bigger fishes to catch.