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The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models
TLDR
A set of simple guidelines for developing validated and predictive QSPR models is presented, highlighting the need to establish the domain of model applicability in the chemical space to flag molecules for which predictions may be unreliable, and some algorithms that can be used for this purpose.
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Principles of QSAR models validation: internal and external
TLDR
Evidence is presented that only models that have been validated externally, after their internal validation, can be considered reliable and applicable for both external prediction and regulatory purposes.
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Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.
This article provides an overview of methods for reliability assessment of quantitative structure-activity relationship (QSAR) models in the context of regulatory acceptance of human health and…
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Real External Predictivity of QSAR Models: How To Evaluate It? Comparison of Different Validation Criteria and Proposal of Using the Concordance Correlation Coefficient
TLDR
The concordance correlation coefficient is proposed as a complementary, or alternative, more prudent measure of a QSAR model to be externally predictive, and works well on real data sets, where it seems to be more stable, and helps in making decisions when the validation measures are in conflict.
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Real External Predictivity of QSAR Models. Part 2. New Intercomparable Thresholds for Different Validation Criteria and the Need for Scatter Plot Inspection
TLDR
This work has studied and compared the general trends of the various criteria relative to different possible biases in external data distributions, using a wide range of different simulated scenarios and proposed new thresholds for each criterion in defining a QSAR model as really externally predictive in a more precautionary approach.
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QSARINS: A new software for the development, analysis, and validation of QSAR MLR models
TLDR
The Insubria Persistent Bioaccumulative and Toxic (PBT) Index model for the prediction of the cumulative behavior of new chemicals as PBTs is implemented and the user can validate single models, predeveloped using also different software.
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Joint algal toxicity of 16 dissimilarly acting chemicals is predictable by the concept of independent action.
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QSAR modeling: where have you been? Where are you going to?
Quantitative structure-activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and…
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Predicting the joint algal toxicity of multi-component s-triazine mixtures at low-effect concentrations of individual toxicants.
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QSARINS‐chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS
A database of environmentally hazardous chemicals, collected and modeled by QSAR by the Insubria group, is included in the updated version of QSARINS, software recently proposed for the development…
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