What is it about?
well as to build new knowledge is here debated. We consider the 3 pillars on which QSAR stands: biological data, chemical knowledge, and modelling algorithms. Most of the time we assume that biological data is a true picture of the world (as they result from good experimental practice), that chemical knowledge is scientifically true, so if a QSAR is not working blame modelling. This opens the way to look at the role of modelling in developing scientific theories, and in producing knowledge. After an excursus in inductive reasoning, we relate the QSAR methodology to open debates in the philosophy of science.
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Why is it important?
QSAR is today in large use in companies and public services. However, as any scientific method, it is nowadays challenged by more and more requests, especially considering its possible role in assessing the safety of new chemicals. Understanding its epistemology is important.
Perspectives
Today the dominant paradigms used to interpret nature are based on Newtonian and Darwinian approaches. Neither are enough to reach a comprehensive description of complex living systems that do not obey the Newtonian view. Biological systems obey specific postulates, where chance and feedback have a role. New models that use the large available data should be actively pursued.
Prof Giuseppina Carla Gini
Politecnico di Milano
Read the Original
This page is a summary of: QSAR: What Else?, January 2018, Springer Science + Business Media,
DOI: 10.1007/978-1-4939-7899-1_3.
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