Author
Franco Lombardo
Bio: Franco Lombardo is an academic researcher from Pfizer. The author has contributed to research in topics: Cholecystokinin B receptor & Recursive partitioning. The author has an hindex of 17, co-authored 25 publications receiving 13952 citations.
Papers
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TL;DR: Experimental and computational approaches to estimate solubility and permeability in discovery and development settings are described in this article, where the rule of 5 is used to predict poor absorption or permeability when there are more than 5 H-bond donors, 10 Hbond acceptors, and the calculated Log P (CLogP) is greater than 5 (or MlogP > 415).
14,026 citations
TL;DR: A guide for stabilization of pharmaceuticals to oxidation is presented and selection of and methods for use of antioxidants are discussed including recommended levels.
Abstract: A guide for stabilization of pharmaceuticals to oxidation is presented. Literature is presented with an attempt to be a ready source for data and recommendations for formulators. Liquid and solid dosage forms are discussed with options including formulation changes, additives, and packaging documented. In particular, selection of and methods for use of antioxidants are discussed including recommended levels.
240 citations
TL;DR: An RP-HPLC method, for the determination of logPoct values for neutral drugs, which combines ease of operation with high accuracy and which has been shown to work for a set of 36 molecules comprised largely of drugs, is presented.
Abstract: We present an RP-HPLC method, for the determination of logPoct values for neutral drugs, which combines ease of operation with high accuracy and which has been shown to work for a set of 36 molecules comprised largely of drugs The general features of the method are as follows: (i) compound sparing (< or = 1 mL of a 30-50 microg/mL solution needed), (ii) rapid determinations (20 min on average), (iii) low sensitivity to impurities, (iv) wide lipophilicity range (6 logPoct units), (v) good accuracy, (vi) excellent reproducibility A linear free energy relationship (LFER) analysis, based on solvation parameters, shows that the method encodes the same information obtained from a shake-flask logPoct determination To the best of our knowledge a similar performance, on a set of noncongeneric drugs, has not been previously reported We refer to the value generated via this method as ElogPoct
236 citations
TL;DR: The ratio of brain-blood partitioning, log(Cbrain/Cblood) (log BB), of a series of compounds that range from simple solutes to histamine H2 antagonists was correlated with computed solvation free energy in water (delta G degree W).
Abstract: The ratio of brain-blood partitioning, log(Cbrain/Cblood) (log BB), of a series of compounds that range from simple solutes to histamine H2 antagonists was correlated with computed solvation free energy in water (delta G degree W). The free energies were computed with the AMSOL 5.0 program using the AM1-SM2.1 solvation model. From a set of 55 compounds, a function was developed in which log BB was related to the free energy of solvation as follows: log BB = 0.054 delta G degree W + 0.43 (r = 0.82 and standard error = 0.41). This correlation provided successful prediction of brain-blood partitioning for compounds outside the training dataset. Furthermore, for a set of 10 drugs, delta G degree W correlated well with literature data for the permeability of endothelial cell monolayers from bovine brain microvessels. In neuroscience drug discovery, the use of computed solvation free energies to predict brain penetration provides a facile method for prioritizing synthetic targets.
192 citations
TL;DR: It was demonstrated that human VD(ss) values could be predicted, on average, within or very close to 2-fold of the actual value, and it offers a rationale for the reduction of the use of animals in pharmacokinetic studies.
Abstract: We present a method for the prediction of volume of distribution in humans, for neutral and basic compounds. It is based on two experimentally determined physicochemical parameters, ElogD(7.4) and f(i(7.4)), the latter being the fraction of compound ionized at pH 7.4 and on the fraction of free drug in plasma (f(u)). The fraction unbound in tissues (f(ut)), determined via a regression analysis from 64 compounds using the parameters described, is then used to predict VD(ss) via the Oie-Tozer equation. Accuracy of this method was determined using a test set of 14 compounds, and it was demonstrated that human VD(ss) values could be predicted, on average, within or very close to 2-fold of the actual value. The present method is as accurate as reported methods based on animal pharmacokinetic data, using a similar set of compounds, and ranges between 1.62 and 2.20 as mean-fold error. This method has the advantage of being amenable to automation, and therefore fast throughput, it is compound and resources sparing, and it offers a rationale for the reduction of the use of animals in pharmacokinetic studies. A discussion of the potential errors that may be encountered, including errors in the determination of f(u), is offered, and the caveats about the use of computed vs experimentally determined logD and pK(a) values are addressed.
179 citations
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TL;DR: This paper identified the small molecule ferrostatin-1 as a potent inhibitor of ferroptosis in cancer cells and glutamate-induced cell death in organotypic rat brain slices, suggesting similarities between these two processes.
7,192 citations
TL;DR: The new SwissADME web tool is presented that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar are presented.
Abstract: To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours.
6,135 citations
Book•
17 May 2013
TL;DR: This research presents a novel and scalable approach called “Smartfitting” that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of designing and implementing statistical models for regression models.
Abstract: General Strategies.- Regression Models.- Classification Models.- Other Considerations.- Appendix.- References.- Indices.
3,672 citations
TL;DR: This topic is explored in terms ofDrug-like physicochemical features, drug-like structural features, a comparison of drug- like and non-drug-like in drug discovery and a discussion of how drug-Like features relate to clinical success.
3,499 citations
TL;DR: A consensus number of current drug targets for all classes of approved therapeutic drugs is proposed, and an emerging realization of the importance of polypharmacology and also the power of a gene-family-led approach in generating novel and important therapies is highlighted.
Abstract: For the past decade, the number of molecular targets for approved drugs has been debated. Here, we reconcile apparently contradictory previous reports into a comprehensive survey, and propose a consensus number of current drug targets for all classes of approved therapeutic drugs. One striking feature is the relatively constant historical rate of target innovation (the rate at which drugs against new targets are launched); however, the rate of developing drugs against new families is significantly lower. The recent approval of drugs that target protein kinases highlights two additional trends: an emerging realization of the importance of polypharmacology, and also the power of a gene-family-led approach in generating novel and important therapies.
3,284 citations