Simulations Plus

Key enhancements include:

• Enhanced Models: New and expanded models offer greater predictive accuracy, with an average 30% increase in training set sizes, for microsome and hepatocyte clearance, protein binding, biorelevant solubilities, MDCK-LE/PAMPA permeability, and more.
• High-Throughput Pharmacokinetics (HTPK): New options for solution dosing, adjusted free fraction outputs, and species-specific simulations enhance the flexibility and precision of HTPK studies.
• Artificial Intelligence-Driven Drug Design (AIDD): Integration of 3D shape matching and tissue sensitivities (based on tissue Kp values) as new objectives, facilitating innovative lead optimization processes.
• New DILI Module: Introduction of the first drug-induced liver injury (DILI) endpoint models to support high-throughput (HT) DILIsym® predictions in early drug development.
• Boosted ANN regression models and 37 new descriptors in ADMET Modeler™
• + more

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• Multiprotic pKa model (S+Acidic_pKa, S+Mixed_pKa, S+Basic_pKa) – a thermodynamically accurate multiprotic model for multiple ionization sites based on atomic descriptors and neural networks – not a database lookup!
• logP (S+logP, MlogP) – log of the octanol to water partition coefficient.  There are two models, an artificial neural network ensemble (S+logP) and Moriguchi (MlogP)
• logD (S+logD) – estimation of octanol-water distribution coefficient at user-defined pH
• Air-water partition (logHLC) – estimation of air-water partition coefficient (Henry’s Law constant) from US EPA data
• Inhibition of the hepatic OATP1B1 transporter in human (OATP1B1_Inh)
• Inhibition of the intestinal P-gp transporter in human (Pgp_Inh)
• Likelihood of intestinal efflux by P-gp transporter in human (Pgp_Substr)

• Human effective permeability (S+Peff) – jejunal Peff
• MDCK apparent permeability (S+MDCK) – in vitro Papp
• Corneal permeability (Perm_Cornea) – ocular permeability through rabbit cornea based on literature data obtained in vitro
• Skin permeability (Perm_Skin) – permeability through human skin of compounds dissolved in aqueous solution; based on literature data
• Blood-brain barrier permeation – there are two models, classification (BBB_Filter) and regression (LogBB).  The first classification model has a low cutoff such that compounds that are predicted to have low permeability have very little chance of penetrating the blood-brain barrier.  Compounds that are predicted to have high blood-brain barrier penetration should be evaluated with the regression model that predicts the blood to brain concentration ratio.

• Human and rat plasma protein binding as percent unbound (hum_fup% and rat_fup%)
• Human volume of distribution (Vd)
• Human and rat blood-to-plasma concentration ratio (RBP and RBP_rat)
• Fraction unbound in human liver microsomes (S+fumic)