Theoretical predictions of drug absorption in drug discovery and development

Beyond cytotoxic potency: disposition features required to design ADC payload

1. Antibody-drug conjugates (ADCs) have demonstrated impressive clinical usefulness in treating several types of cancer, with the notion of widening of the therapeutic index of the cytotoxic payload through the minimisation of the systemic toxicity. Therefore, choosing the most appropriate payload molecule is a particularly important part of the early design phase of ADC development, especially given the highly competitive environment ADCs find themselves in today.2. The focus of the current review is to describe critical attributes/considerations needed in the discovery and ultimately development of cytotoxic payloads in support of ADC design. In addition to potency, several key dispositional characteristics including solubility, permeability and bystander effect, pharmacokinetics, metabolism, and drug-drug interactions, are described as being an integral part of the integrated activities required in the design of clinically safe and useful ADC therapeutic agents.

Advances in Modeling Approaches for Oral Drug Delivery: Artificial Intelligence, Physiologically-Based Pharmacokinetics, and First-Principles Models

Oral drug absorption is the primary route for drug administration. However, this process hinges on multiple factors, including the drug's physicochemical properties, formulation characteristics, and gastrointestinal physiology. Given its intricacy and the exorbitant costs associated with experimentation, the trial-and-error method proves prohibitively expensive. Theoretical models have emerged as a cost-effective alternative by assimilating data from diverse experiments and theoretical considerations. These models fall into three categories: (i) data-driven models, encompassing classical pharmacokinetics, quantitative-structure models (QSAR), and machine/deep learning; (ii) mechanism-based models, which include quasi-equilibrium, steady-state, and physiologically-based pharmacokinetics models; and (iii) first principles models, including molecular dynamics and continuum models. This review provides an overview of recent modeling endeavors across these categories while evaluating their respective advantages and limitations. Additionally, a primer on partial differential equations and their numerical solutions is included in the appendix, recognizing their utility in modeling physiological systems despite their mathematical complexity limiting widespread application in this field.

Improving the Accuracy of Permeability Data to Gain Predictive Power: Assessing Sources of Variability in Assays Using Cell Monolayers

The ability to predict the rate of permeation of new compounds across biological membranes is of high importance for their success as drugs, as it determines their efficacy, pharmacokinetics, and safety profile. In vitro permeability assays using Caco-2 monolayers are commonly employed to assess permeability across the intestinal epithelium, with an extensive number of apparent permeability coefficient (Papp) values available in the literature and a significant fraction collected in databases. The compilation of these Papp values for large datasets allows for the application of artificial intelligence tools for establishing quantitative structure-permeability relationships (QSPRs) to predict the permeability of new compounds from their structural properties. One of the main challenges that hinders the development of accurate predictions is the existence of multiple Papp values for the same compound, mostly caused by differences in the experimental protocols employed. This review addresses the magnitude of the variability within and between laboratories to interpret its impact on QSPR modelling, systematically and quantitatively assessing the most common sources of variability. This review emphasizes the importance of compiling consistent Papp data and suggests strategies that may be used to obtain such data, contributing to the establishment of robust QSPRs with enhanced predictive power.

Sustainable methods for the carboxymethylation and methylation of ursolic acid with dimethyl carbonate under mild and acidic conditions

Ursolic acid is a triterpene plant extract that exhibits significant potential as an anti-cancer, anti-tumour, and anti-inflammatory agent. Its direct use in the pharmaceutical industry is hampered by poor uptake of ursolic acid in the human body coupled with rapid metabolism causing a decrease in bioactivity. Modification of ursolic acid can overcome such issues, however, use of toxic reagents, unsustainable synthetic routes and poor reaction metrics have limited its potential. Herein, we demonstrate the first reported carboxymethylation and/or methylation of ursolic acid with dimethyl carbonate (DMC) as a green solvent and sustainable reagent under acidic conditions. The reaction of DMC with ursolic acid, in the presence of PTSA, ZnCl2, or H2SO4-SiO2 yielded the carboxymethylation product 3β-[[methoxy]carbonyl]oxyurs-12-en-28-oic acid, the methylation product 3β-methoxyurs-12-en-28-oic acid and the dehydration product urs-2,12-dien-28-oic acid. PTSA demonstrated high conversion and selectivity towards the previously unreported carboxymethylation of ursolic acid, while the application of formic acid in the system led to formylation of ursolic acid (3β-formylurs-12-en-28-oic acid) in quantitative yields via esterification, with DMC acting solely as a solvent. Meanwhile, the methylation product of ursolic acid, 3β-methoxyurs-12-en-28-oic acid, was successfully synthesised with FeCl3, demonstrating exceptional conversion and selectivity, >99% and 99%, respectively. Confirmed with the use of qualitative and quantitative green metrics, this result represents a significant improvement in conversion, selectivity, safety, and sustainability over previously reported methods of ursolic acid modification. It was demonstrated that these methods could be applied to other triterpenoids, including corosolic acid. The study also explored the potential pharmaceutical applications of ursolic acid, corosolic acid, and their derivatives, particularly in anti-inflammatory, anti-cancer, and anti-tumour treatments, using molecular ADMET and docking methods. The methods developed in this work have led to the synthesis of novel molecules, thus creating opportunities for the future investigation of biological activity and the modification of a wide range of triterpenoids applying acidic DMC systems to deliver novel active pharmaceutical intermediates.

The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery

Drug discovery and development are aimed at identifying new chemical molecular entities (NCEs) with desirable pharmacokinetic profiles for high therapeutic efficacy. The plasma concentrations of NCEs are a biomarker of their efficacy and are governed by pharmacokinetic processes such as absorption, distribution, metabolism, and excretion (ADME). Poor ADME properties of NCEs are a major cause of attrition in drug development. ADME screening is used to identify and optimize lead compounds in the drug discovery process. Computational models predicting ADME properties have been developed with evolving model-building technologies from a simplified relationship between ADME endpoints and physicochemical properties to machine learning, including support vector machines, random forests, and convolution neural networks. Recently, in the field of in silico ADME research, there has been a shift toward evaluating the in vivo parameters or plasma concentrations of NCEs instead of using predictive results to guide chemical structure design. Another research hotspot is the establishment of a computational prediction platform to strengthen academic drug discovery. Bioinformatics projects have produced a series of in silico ADME models using free software and open-access databases. In this review, we introduce prediction models for various ADME parameters and discuss the currently available academic drug discovery platforms.

GC-MS Analysis, Molecular Docking and Pharmacokinetic Properties of Phytocompounds from Solanum torvum Unripe Fruits and Its Effect on Breast Cancer Target Protein

This study was designed to identify phytocompounds from the aqueous extract of Solanum torvum unripe fruits using GC–MS analysis against breast cancer. For this, the identified phytocompounds were subjected to perform molecular docking studies to find the effects on breast cancer target protein. Pharmacokinetic properties were also tested for the identified phytocompounds to evaluate the ADMET properties. Molecular docking studies were done using docking software PyRx, and pharmacokinetic properties of phytocompounds were evaluated using SwissADME. From the results, ten best compounds were identified from GC–MS analysis against breast cancer target protein. Of which, three compounds showed very good binding affinity with breast cancer target protein. They are ergost-25-ene-3,6-dione,5,12-dihydroxy-,(5.alpha.,12.beta.) (− 7.3 kcal/mol), aspidospermidin-17-ol,1-acetyl-16-methoxy (− 6.7 kcal/mol) and 2-(3,4-dichlorophenyl)-4-[[2-[1-methyl-2-pyrrolidinyl]ethyl amino]-6-[trichloromethyl]-s-triazine (− 6.7 kcal/mol). Further, docking study was performed for the synthetic drug doxorubicin to compare the efficiency of phytocompounds. The binding affinity of ergost-25-ene-3,6-dione,5,12-dihydroxy-,(5.alpha.,12.beta.) is higher than the synthetic drug doxorubicin (− 7.2 kcal/mol), and the binding affinity of other compounds is also very near to the drug. Hence, the present study concludes that the phytocompounds from the aqueous extract of Solanum torvum unripe fruits have the potential ability to treat breast cancer.

The Target Determination and the Mechanism of Action of Chiral-Antimalarial Drugs: A Docking Approach

Due to an undecided target and the prescription of chiral-aminoquinolines (chloroquine, primaquine and quinacrine) in the racemic form, the mechanism of action as well as the reason of causing side effects become unclear. Based on computationally evaluated literature data, the things determined theoretically were (i) the target of aminoquinolines during antimalarial activity, (ii) the mechanism of action of chiral-aminoquinolines and (iii) biologically active enantiomers of aminoquinolines. For the presented study, the enantiomeric binding affinities of aminoquinolines with all the targets claimed by other scientists were calculated, and then used in interpretation with the help of many investigations done/observed by others. The results were very interesting based on which, a new and acceptable mechanism of action of chiral-aminoquinolines during malaria curing step, is given for the first time. The current docking study not only resolves the questionable point about a definite target of aminoquinolines but also makes the mechanism of action understandable.

Segmental-Dependent Intestinal Drug Permeability: Development and Model Validation of In Silico Predictions Guided by In Vivo Permeability Values

The goal of this work was to develop an in silico model that allows predicting segmental-dependent permeability throughout the small intestine (SI). In vivo permeability of 11 model drugs in 3 SI segments (jejunum, mid-SI, ileum) was studied in rats, creating a data set that reflects the conditions throughout the SI. Then, a predictive model was developed, combining physicochemical drug properties influencing the underlying mechanism of passive permeability: Log p, polar surface area, M_W, H-bond count, and Log f_u, with microenvironmental SI conditions. Excellent correlation was evident between the predicted and experimental data (R² = 0.914), with similar predictability in each SI segment. Log p and Log f_u were identified as the major determinants of permeability, with similar contribution. Total H-bond count was also a significant determinant, followed by polar surface area and M_W. Leaving out any of the model parameters decreased its predictability. The model was validated against 5 external drugs, with excellent predictability. Notably, the model was able to predict the segmental-dependent permeability of all drugs showing this trend experimentally. Model predictability was better in the high-permeability versus low-permeability range. Overall, our approach of constructing a straightforward in silico model allowed reliable predictions of segmental-dependent intestinal permeability, providing new insights into relative effects of drug-related factors and gastrointestinal environment on permeability.

Pharmacokinetics Studies of 12 Alkaloids in Rat Plasma after Oral Administration of Zuojin and Fan-Zuojin Formulas

Zuojin formula (ZJ) is a traditional Chinese medicine (TCM) prescription consisted of Coptidis Rhizoma (CR) and Euodiae Fructus (EF), and has been used to treat gastrointestinal (GI) disease for more than 700 years. Fan-Zuojin formula (FZJ) is a related TCM prescription also consisted of CR and EF with the opposite proportion. In recent years, ZJ was getting more attention for its antitumor potential, but the indeterminate pharmacokinetic (PK) behavior restricted its clinical applications, and the PK differences between ZJ and FZJ were also largely unknown. Consequently it is necessary to carry out a full-scale PK study to demonstrate the physiological disposition of ZJ, as well as the comparative PK study between ZJ and FZJ to illustrate the compatibility dose effects. Therefore a liquid chromatographic–tandem mass spectrometry (LC–MS/MS) method was established and validated for the determinations of coptisine, epiberberine, palmatine, berberine, 8-oxocoptisine, 8-oxoepiberberine, noroxyhydrastinine, corydaldine, dehydroevodiamine, evodiamine, wuchuyuamide-I, and evocarpine in rat plasma. PK characteristics of 12 alkaloids after oral administration of ZJ and FZJ were compared, and the result was analyzed and discussed with the help of an in silico study. Then an integrated PK study was carried out with the AUC-based weighting method and the total drug concentration method. The established method has been successfully applied to reveal the PK profiles of the 12 alkaloids in rat plasma after oral administration of ZJ and FZJ. The results showed that: (1) double peaks were observed in the plasma concentration-time (C–T) curves of the alkaloids after ZJ administration; but the C–T curves approximately matched the two-compartment model after FZJ administration; (2) There were wide variations in the absorption levels of these alkaloids; and even for a certain alkaloid, the dose modified systemic exposure levels and elimination rate also varied significantly after administration of ZJ and FZJ extracts. The results could be interpreted as follows: firstly, inhibition effect on GI motility caused by the high content CR alkaloids (especially berberine) in ZJ could delay the T_max, and increase the absorption and systemic exposure levels of the other alkaloids, and also lead to the double peak phenomenon of these alkaloids. However, for quaternary protoberberine alkaloids (QPA), double peaks were primarily caused by the different Ka value in two intestinal absorption sites; Secondly, absorption was the major obstacle to the systemic exposure level of the alkaloids from CR and EF. In silico and PK studies suggested that the absorption of these alkaloids, except QPAs, mainly depended on their solubility rather than permeability; Thirdly, EF could promote the absorption and accelerate the elimination of QPAs, and had a greater influence on the former than the latter. At last the integrated PK analysis suggested that berberine and dehydroevodiamine could be regarded as the representative components to reflect the PK behaviors of CR and EF alkaloids after administration of ZJ and FZJ. In conclusion, the absorption, elimination and systemic exposure level of these alkaloids were mainly influenced by the proportion of EF and CR, the pharmacological effect on GI motility, and the physicochemical property of these alkaloids. These findings would be helpful for a better understanding of the activities and clinical applications of ZJ, FZJ and other related TCM prescriptions.

BCS class IV drugs: Highly notorious candidates for formulation development

BCS class IV drugs (e.g., amphotericin B, furosemide, acetazolamide, ritonavir, paclitaxel) exhibit many characteristics that are problematic for effective oral and per oral delivery. Some of the problems associated include low aqueous solubility, poor permeability, erratic and poor absorption, inter and intra subject variability and significant positive food effect which leads to low and variable bioavailability. Also, most of the class IV drugs are substrate for P-glycoprotein (low permeability) and substrate for CYP3A4 (extensive pre systemic metabolism) which further potentiates the problem of poor therapeutic potential of these drugs. A decade back, extreme examples of class IV compounds were an exception rather than the rule, yet today many drug candidates under development pipeline fall into this category. Formulation and development of an efficacious delivery system for BCS class IV drugs are herculean tasks for any formulator. The inherent hurdles posed by these drugs hamper their translation to actual market. The importance of the formulation composition and design to successful drug development is especially illustrated by the BCS class IV case. To be clinically effective these drugs require the development of a proper delivery system for both oral and per oral delivery. Ideal oral dosage forms should produce both a reasonably high bioavailability and low inter and intra subject variability in absorption. Also, ideal systems for BCS class IV should produce a therapeutic concentration of the drug at reasonable dose volumes for intravenous administration. This article highlights the various techniques and upcoming strategies which can be employed for the development of highly notorious BCS class IV drugs. Some of the techniques employed are lipid based delivery systems, polymer based nanocarriers, crystal engineering (nanocrystals and co-crystals), liquisolid technology, self-emulsifying solid dispersions and miscellaneous techniques addressing the P-gp efflux problem. The review also focuses on the roadblocks in the clinical development of the aforementioned strategies such as problems in scale up, manufacturing under cGMP guidelines, appropriate quality control tests, validation of various processes and variable therein etc. It also brings to forefront the current lack of regulatory guidelines which poses difficulties during preclinical and clinical testing for submission of NDA and subsequent marketing. Today, the pharmaceutical industry has as its disposal a series of reliable and scalable formulation strategies for BCS Class IV drugs. However, due to lack of understanding of the basic physical chemistry behind these strategies formulation development is still driven by trial and error.

When barriers ignore the "rule-of-five"

Why are a few drugs with properties beyond the rule of 5 (bRo5) absorbed across the intestinal mucosa while most other bRo5 compounds are not? Are such exceptional bRo5 compounds exclusively taken up by carrier-mediated transport or are they able to permeate the lipid bilayer (passive lipoidal diffusion)? Our experimental data with liposomes indicate that tetracycline, which violates one rule of the Ro5, and rifampicin, violating three of the rules, significantly permeate a phospholipid bilayer with kinetics similar to labetalol and metoprolol, respectively. Published data from experimental work and molecular dynamics simulations suggest that the formation of intramolecular H-bonds and the possibility to adopt an elongated shape besides the presence of a significant fraction of net neutral species facilitate lipid bilayer permeation. As an alternative to lipid bilayer permeation, carrier proteins can be targeted to improve absorption, with the potential drawbacks of drug-drug interactions and non-linear pharmacokinetics.

Predicting binding affinities of diverse pharmaceutical chemicals to human serum plasma proteins using QSPR modelling approaches

The prediction of the plasma protein binding (PPB) affinity of chemicals is of paramount significance in the drug development process. In this study, ensemble machine learning-based QSPR models have been established for a four-category classification and PPB affinity prediction of diverse compounds using a large PPB dataset of 930 compounds and in accordance with the OECD guidelines. The structural diversity of the chemicals was tested by the Tanimoto similarity index. The external predictive power of the developed QSPR models was evaluated through internal and external validations. In the QSPR models, XLogP was the most important descriptor. In the test data, the classification QSPR models rendered an accuracy of >93%, while the regression QSPR models yielded r(2) of >0.920 between the measured and predicted PPB affinities, with the root mean squared error <9.77. Values of statistical coefficients derived for the test data were above their threshold limits, thus put a high confidence in this analysis. The QSPR models in this study performed better than any of the previous studies. The results suggest that the developed QSPR models are reliable for predicting the PPB affinity of structurally diverse chemicals. They can be useful for initial screening of candidate molecules in the drug development process.

In silico ADME/T modelling for rational drug design

In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.

Clustered distribution of natural product leads of drugs in the chemical space as influenced by the privileged target-sites

Some natural product leads of drugs (NPLDs) have been found to congregate in the chemical space. The extent, detailed patterns, and mechanisms of this congregation phenomenon have not been fully investigated and their usefulness for NPLD discovery needs to be more extensively tested. In this work, we generated and evaluated the distribution patterns of 442 NPLDs of 749 pre-2013 approved and 263 clinical trial small molecule drugs in the chemical space represented by the molecular scaffold and fingerprint trees of 137,836 non-redundant natural products. In the molecular scaffold trees, 62.7% approved and 37.4% clinical trial NPLDs congregate in 62 drug-productive scaffolds/scaffold-branches. In the molecular fingerprint tree, 82.5% approved and 63.0% clinical trial NPLDs are clustered in 60 drug-productive clusters (DCs) partly due to their preferential binding to 45 privileged target-site classes. The distribution patterns of the NPLDs are distinguished from those of the bioactive natural products. 11.7% of the NPLDs in these DCs have remote-similarity relationship with the nearest NPLD in their own DC. The majority of the new NPLDs emerge from preexisting DCs. The usefulness of the derived knowledge for NPLD discovery was demonstrated by the recognition of the new NPLDs of 2013-2014 approved drugs.

Tyrosine-derived polycarbonate-silica xerogel nanocomposites for controlled drug delivery

Biodegradable polymer-ceramic composites offer significant potential advantages in biomedical applications where the properties of either polymers or ceramics alone are insufficient to meet performance requirements. Here we demonstrate the highly tunable mechanical and controlled drug delivery properties accessible with novel biodegradable nanocomposites prepared by non-covalent binding of silica xerogels and co-polymers of tyrosine-poly(ethylene glycol)-derived poly(ether carbonate). The Young's moduli of the nanocomposites exceed by factors of 5-20 times those of the co-polymers or of composites made with micron scale silica particles. Increasing the fraction of xerogel in the nanocomposites increases the glass transition temperature and the mechanical strength, but decreases the equilibrium water content, which are all indicative of strong non-covalent interfacial interactions between the co-polymers and the silica nanoparticles. Sustained, tunable controlled release of both hydrophilic and hydrophobic therapeutic agents from the nanocomposites is demonstrated with two clinically significant drugs, rifampicin and bupivacaine. Bupivacaine exhibits an initial small burst release followed by slow release over the 7 day test period. Rifampicin release fits the diffusion-controlled Higuchi model and the amount released exceeds the dosage required for treatment of clinically challenging infections. These nanocomposites are thus attractive biomaterials for applications such as wound dressings, tissue engineering substrates and stents.

Keeping a critical eye on the science and the regulation of oral drug absorption: a review

This review starts with an introduction on the theoretical aspects of biopharmaceutics and developments in this field from mid-1950s to late 1970s. It critically addresses issues related to fundamental processes in oral drug absorption such as the complex interplay between drugs and the gastrointestinal system. Special emphasis is placed on drug dissolution and permeability phenomena as well as on the mathematical modeling of oral drug absorption. The review ends with regulatory aspects of oral drug absorption focusing on bioequivalence studies and the US Food and Drug Administration and European Medicines Agency guidelines dealing with Biopharmaceutics Classification System and Biopharmaceutic Drug Disposition Classification System.

Intelligent, self-powered, drug delivery systems

Self-propelled nano/micromotors and pumps are considered to be next generation drug delivery systems since the carriers can either propel themselves ("motor"-based drug delivery) or be delivered ("pump"-based drug delivery) to the target in response to specific biomarkers. Recently, there has been significant advancement towards developing nano/microtransporters into proof-of-concept tools for biomedical applications. This review encompasses the progress made to date on the design of synthetic nano/micromotors and pumps with respect to transportation and delivery of cargo at specific locations. Looking ahead, it is possible to imagine a day when intelligent machines navigate through the human body and perform challenging tasks.

The solubility-permeability interplay and its implications in formulation design and development for poorly soluble drugs

While each of the two key parameters of oral drug absorption, the solubility and the permeability, has been comprehensively studied separately, the relationship and interplay between the two have been largely ignored. For instance, when formulating a low-solubility drug using various solubilization techniques: what are we doing to the apparent permeability when we increase the solubility? Permeability is equal to the drug's diffusion coefficient through the membrane times the membrane/aqueous partition coefficient divided by the membrane thickness. The direct correlation between the intestinal permeability and the membrane/aqueous partitioning, which in turn is dependent on the drug's apparent solubility in the GI milieu, suggests that the solubility and the permeability are closely associated, exhibiting a certain interplay between them, and the current view of treating the one irrespectively of the other may not be sufficient. In this paper, we describe the research that has been done thus far, and present new data, to shed light on this solubility-permeability interplay. It has been shown that decreased apparent permeability accompanies the solubility increase when using different solubilization methods. Overall, the weight of the evidence indicates that the solubility-permeability interplay cannot be ignored when using solubility-enabling formulations; looking solely at the solubility enhancement that the formulation enables may be misleading with regards to predicting the resulting absorption, and hence, the solubility-permeability interplay must be taken into account to strike the optimal solubility-permeability balance, in order to maximize the overall absorption.

Attenuation of intestinal absorption by major efflux transporters: quantitative tools and strategies using a Caco-2 model

Efflux transporters expressed in the apical membrane of intestinal enterocytes have been implicated in drug oral absorption. The current study presents a strategy and tools to quantitatively predict the impact of efflux on oral absorption for new chemical entities (NCEs) in early drug discovery. Sixty-three marketed drugs with human absorption data were evaluated in the Caco-2 bidirectional permeability assay and subjected to specific transporter inhibition. A four-zone graphical model was developed from apparent permeability and efflux ratios to quickly identify compounds whose efflux activity may distinctly influence human absorption. NCEs in "zone 4" will probably have efflux as a barrier for oral absorption and further mechanistic studies are required. To interpret mechanistic results, we introduced a new quantitative substrate classification parameter, transporter substrate index (TSI). TSI allowed more flexibility and considered both in vitro and in vivo outcomes. Its application ranged from addressing the challenge of overlapping substrate specificity to projecting the role of transporter(s) on exposure or potential drug-drug interaction risk. The potential impact of efflux transporters associated with physicochemical properties on drug absorption is discussed in the context of TSI and also the previously reported absorption quotient. In this way, the chemistry strategy may be differentially focused on passive permeability or efflux activity or both.

An evaluation of the relative roles of the unstirred water layer and receptor sink in limiting the in-vitro intestinal permeability of drug compounds of varying lipophilicity

The roles of the unstirred water layer (UWL) and receptor sink on the in-vitro transmembrane permeability of an increasingly lipophilic series of compounds (mannitol (MAN), diazepam (DIA) and cinnarizine (CIN)) have been assessed. Altered carbogen bubbling rates were used as a means to change the UWL thickness and polysorbate-80 (PS-80), bovine serum albumin (BSA) and α-1-acid glycoprotein (AAG) were employed to alter sink conditions. After correction for solubilisation, Papp data for MAN, DIA and CIN were consistent across varying donor PS-80 concentrations suggesting that for the drugs examined here, the donor UWL did not limit in-vitro permeability. Similarly, altered bubbling rates and receptor sink conditions had no impact on the permeability of MAN. In contrast, decreasing the size of the receptor UWL or adding solubilising agents to the receptor sink resulted in modest enhancements to the permeability of the more lipophilic probe DIA. For the most lipophilic compound, CIN, very significant changes to measured permeability (&gt;30 fold) were possible, but were most evident only after concomitant changes to both the UWL and sink conditions, suggesting that the effectiveness of enhanced sink conditions were dependent on a decrease in the width of the UWL.

Prediction of human pharmacokinetics — renal metabolic and excretion clearance

The kidneys have the capability to both excrete and metabolise drugs. An understanding of mechanisms that determine these processes is required for the prediction of pharmacokinetics, exposures, doses and interactions of candidate drugs. This is particularly important for compounds predicted to have low or negligible non-renal clearance (CL). Clinically significant interactions in drug transport occur mostly in the kidneys. The main objective was to evaluate methods for prediction of excretion and metabolic renal CL (CLR) in humans. CLR is difficult to predict because of the involvement of bi-directional passive and active tubular transport, differences in uptake capacity, pH and residence time on luminal and blood sides of tubular cells, and limited knowledge about regional tubular residence time, permeability (Pe) and metabolic capacity. Allometry provides poor predictions of excretion CLR because of species differences in unbound fraction, urine pH and active transport. The correlation between fraction excreted unchanged in urine (fe) in humans and animals is also poor, except for compounds with high passive Pe (extensive/complete tubular reabsorption; zero/negligible fe) and/or high non-renal CL. Physiologically based in-vitro/in-vivo methods could potentially be useful for predicting CLR. Filtration could easily be predicted. Prediction of tubular secretion CL requires an in-vitro transport model and establishment of an in-vitro/in-vivo relationship, and does not appear to have been attempted. The relationship between passive Pe and tubular fraction reabsorbed (freabs) for compounds with and without apparent secretion has recently been established and useful equations and limits for prediction were developed. The suggestion that reabsorption has a lipophilicity cut-off does not seem to hold. Instead, compounds with passive Pe that is less than or equal to that of atenolol are expected to have negligible passive freabs. Compounds with passive Pe that is equal to or higher than that of carbamazepine are expected to have complete freabs. For compounds with intermediate Pe the relationship is irregular and freabs is difficult to predict. Tubular cells are comparably impermeable (for passive diffusion), and show regional differences in enzymatic and transporter activities. This limits the usefulness of microsome data and makes microsome-based predictions of metabolic CLR questionable. Renal concentrations and activities of CYP450s are comparably low, suggesting that CYP450 substrates have negligible metabolic CLR. The metabolic CLR of high-Pe UDP-glucuronyltransferase substrates could contribute to the total CL.

Ionization-specific analysis of human intestinal absorption

This study presents a mechanistic QSAR analysis of human intestinal absorption of drugs and drug-like compounds using a data set of 567 %HIA values. Experimental data represent passive diffusion across intestinal membranes, and are considered to be reasonably free of carrier-mediated transport or other unwanted effects. A nonlinear model was developed relating %HIA to physicochemical properties of drugs (lipophilicity, ionization, hydrogen bonding, and molecular size). The model describes ion-specific intestinal permeability of drugs by both transcellular and paracellular routes, and also accounts for unstirred water layer effects. The obtained model was validated on two external data sets consisting of in vivo human jejunal permeability coefficients (P(eff)) and absorption rate constants (K(a)). Validation results demonstrate good predictive power of the model (RMSE = 0.35-0.45 log units for log K(a) and log P(eff)). High prediction accuracy together with clear physicochemical interpretation (log P, pK(a)) makes this model particularly suitable for use in property-based drug design.

Nanovehicular intracellular delivery systems

This article provides an overview of principles and barriers relevant to intracellular drug and gene transport, accumulation and retention (collectively called as drug delivery) by means of nanovehicles (NV). The aim is to deliver a cargo to a particular intracellular site, if possible, to exert a local action. Some of the principles discussed in this article apply to noncolloidal drugs that are not permeable to the plasma membrane or to the blood-brain barrier. NV are defined as a wide range of nanosized particles leading to colloidal objects which are capable of entering cells and tissues and delivering a cargo intracelullarly. Different localization and targeting means are discussed. Limited discussion on pharmacokinetics and pharmacodynamics is also presented. NVs are contrasted to micro-delivery and current nanotechnologies which are already in commercial use. Newer developments in NV technologies are outlined and future applications are stressed. We also briefly review the existing modeling tools and approaches to quantitatively describe the behavior of targeted NV within the vascular and tumor compartments, an area of particular importance. While we list "elementary" phenomena related to different level of complexity of delivery to cancer, we also stress importance of multi-scale modeling and bottom-up systems biology approach.

Prediction of drug solubility from molecular structure using a drug-like training set

Using a training set of 191 drug-like compounds extracted from the AQUASOL database a quantitative structure-property relationship (QSPR) study was conducted employing a set of simple structural and physicochemical properties to predict aqueous solubility. The resultant regression model comprised five parameters (ClogP, molecular weight, indicator variable for aliphatic amine groups, number of rotatable bonds and number of aromatic rings) and demonstrated acceptable statistics (r2 = 0.87, s = 0.51, F = 243.6, n = 191). The model was applied to two test sets consisting of a drug-like set of compounds (r2 = 0.80, s = 0.68, n = 174) and a set of agrochemicals (r2 = 0.88, s = 0.65, n = 200). Using the established general solubility equation (GSE) on the training and drug-like test set gave poorer results than the current study. The agrochemical test set was predicted with equal accuracy using the GSE and the QSPR equation. The results of this study suggest that increasing molecular size, rigidity and lipophilicity decrease solubility whereas increasing conformational flexibility and the presence of a non-conjugated amine group increase the solubility of drug-like compounds. Indeed, the proposed structural parameters make physical sense and provide simple guidelines for modifying solubility during lead optimisation.

Flavonoids induce HIF-1alpha but impair its nuclear accumulation and activity

Hypoxia-inducible factor-1alpha (HIF-1alpha) is the regulatory subunit of the transcription factor HIF-1, which is highly involved in the pathology of diseases associated with tissue hypoxia. In this study we investigated the ability of plant flavonoids to induce HIF-1alpha and regulate HIF-1 transcriptional activity in HeLa cells. We demonstrate for the first time that the flavonoids baicalein, luteolin and fisetin, as well as the previously investigated quercetin, induce HIF-1alpha under normal oxygen pressure, whereas kaempferol, taxifolin, and rutin are inactive. We further reveal that the capability of flavonoids to bind efficiently intracellular iron and their lipophilicity are essential for HIF-1alpha induction. Despite the ability of flavonoids to stabilize HIF-1alpha, the transcriptional activity of HIF-1 induced by flavonoids was significantly lower than that observed with the iron chelator and known HIF-1 inducer, desferrioxamine (DFO). Furthermore, when cells in which HIF-1 had been induced by DFO were also treated with flavonoids, the transcriptional activity of HIF-1 was strongly impaired without simultaneous reduction in HIF-1alpha protein levels. Localization of HIF-1alpha by immuno- and direct fluorescence microscopy and in vitro phosphorylation assays suggest that flavonoids inhibit HIF-1 activity by impairing the MAPK-dependent phosphorylation of HIF-1alpha, thereby decreasing its nuclear accumulation.

ADME evaluation in drug discovery. 7. Prediction of oral absorption by correlation and classification

A critically evaluated database of human intestinal absorption for 648 chemical compounds is reported in this study, among which 579 are believed to be transported by passive diffusion. The correlation analysis between the intestinal absorption and several important molecular properties demonstrated that no single molecular property could be used as a good discriminator to efficiently distinguish the poorly absorbed compounds from those that are well absorbed. The theoretical correlation models for a training set of 455 compounds were proposed by using the genetic function approximation technique. The best prediction model contains four molecular descriptors: topological polar surface area, the predicted distribution coefficient at pH = 6.5, the number of violations of the Lipinski's rule-of-five, and the square of the number of hydrogen-bond donors. The model was able to predict the fractional absorption with an r = 0.84 and a prediction error (absolute mean error) of 11.2% for the training set. Moreover, it achieves an r = 0.90 and a prediction error of 7.8% for a 98-compound test set. The recursive partitioning technique was applied to find the simple hierarchical rules to classify the compounds into poor (%FA < or = 30%) and good (%FA > 30%) intestinal absorption classes. The high quality of the classification model was validated by the satisfactory predictions on the training set (correctly identifying 95.9% of the compounds in the poor-absorption class and 96.1% of the compounds in the good-absorption class) and on the test set (correctly identifying 100% of the compounds in the poor-absorption class and 96.8% of the compounds in the good-absorption class). We expect that, in the future, the rules for the prediction of carrier-mediated transporting and first pass metabolism can be integrated into the current hierarchical rules, and the classification model may become more powerful in the prediction of intestinal absorption or even human bioavailability. The databases of human intestinal absorption reported here are available for download from the supporting Web site: http://modem.ucsd.edu/adme.

Strategies to improve oral drug bioavailability

Efforts to improve oral drug bioavailability have grown in parallel with the pharmaceutical industry. As the number and chemical diversity of drugs has increased, new strategies have been required to develop orally active therapeutics. The past two decades have been characterised by an increased understanding of the causes of low bioavailability and a great deal of innovation in oral drug delivery technologies, marked by an unprecedented growth of the drug delivery industry. The advent of biotechnology and consequent proliferation of biopharmaceuticals have brought new challenges to the drug delivery field. In spite of the difficulties associated with developing oral forms of this type of therapeutics, significant progress has been made in the past few years, with some oral proteins, peptides and other macromolecules currently advancing through clinical trials. This article reviews the approaches that have been successfully applied to improve oral drug bioavailability, primarily, prodrug strategies, lead optimisation through medicinal chemistry and formulation design. Specific strategies to improve the oral bioavailability of biopharmaceuticals are also discussed.

Study of interaction between ibuprofen and nicotinamide using differential scanning calorimetry, spectroscopy, and microscopy and formulation of a fast-acting and possibly better ibuprofen suspension for osteoarthritis patients

Solid-state interaction between ibuprofen and nicotinamide was studied using thermal, spectroscopic, and microscopic techniques. Solubility enhancement was calculated by high-performance liquid chromatography and suspension was found to be the suitable choice of formulation. Ibuprofen-nicotinamide binary mixtures were prepared by solvent evaporation method. Differential scanning calorimetry was used to investigate the stoichiometry and thermal properties of the complex between ibuprofen and nicotinamide. A sharp, single endotherm was observed between the melting endotherms of the individual components at a composition of 60% ibuprofen and 40% nicotinamide (w/w). Several spectroscopic techniques such as ultraviolet-visible, Fourier transform infrared, nuclear magnetic resonance, and powder X-ray diffraction were used to investigate the type of interaction between the two components. Optical microscopy was performed to observe changes with regard to particle size and crystal habit. It was concluded that the interaction that occurred was Pi donor-Pi acceptor in nature and too weak to sustain the integrity of the complex in the liquid state. The solubility of ibuprofen was enhanced by 62 times in the suspension when the concentration of nicotinamide was 13.3 mg/mL. The suspension prepared in this study has potential of being a better medication for pain relief in patients with osteoarthritis.

A novel oral vehicle for poorly soluble HSV-helicase inhibitors: PK/PD validations

PURPOSE

The current study describes the design and validation of a novel oral vehicle for delivering poorly water-soluble herpes simplex virus (HSV)-helicase inhibitors in preclinical pharmacokinetic (PK) and pharmacodynamic (PD) evaluations.

METHODS

Poorly water-soluble compounds were used in solubility and drinking compliance tests in mice. A preferred vehicle containing 0.1% bovine serum albumin (BSA), 3% dextrose, 5% polyethylene glycol (PEG) 400, and 2% peanut oil, pH 2.8 with HCL (BDPP) was selected. This vehicle was further validated with oral PK and in vivo antiviral PD studies using BILS 45 BS.

RESULTS

Solubility screen and drinking compliance tests revealed that the BDPP vehicle could solubilize BILS compounds at 0.5-3 mg/ml concentration range and could be administered to mice without reducing water consumption. Comparative oral PK of BILS 45 BS in HCL or BDPP by gavage at 40 mg/kg showed overlapping PK profiles. In vivo antiviral efficacy and potency of BILS 45 BS in BDPP by oral gavages or in drinking water were confirmed to be comparable as that achieved by gavage in HCL solution.

CONCLUSIONS

These results provide a protein-enriched novel oral vehicle for delivering poorly water-soluble antiviral compounds in a continuous administration mode. Similar approaches may be applicable to other poorly soluble compounds by gavage or in drinking solution.

Predicting the intestinal absorption potential of hits and leads

Today's pharma environment requires rapid and reliable methods of screening drug leads for intestinal permeability potential in the early stages of drug discovery. Techniques using excised tissues, Caco-2 cells, artificial membranes, 'in silico' techniques and surface plasmon resonance (SPR)-based biosensors are critically examined in terms of their reliability, measurement criteria, throughput and utility in identifying potentially successful or unsuccessful drug molecules.:

Accuracy of calculated pH-dependent aqueous drug solubility

The aim of the present study was to investigate the extent to which the Henderson-Hasselbalch (HH) relationship can be used to predict the pH-dependent aqueous solubility of cationic drugs. The pH-dependent solubility for 25 amines, carrying a single positive charge, was determined with a small-scale shake flask method. Each sample was prepared as a suspension in 150 mM phosphate buffer. The pH-dependent solubility curves were obtained using at least 10 different pH values. The intrinsic solubility, the solubility at the pKa and the solubility at pH values reflecting the pH of the bulk and acid microclimate in the human small intestine (pH 7.4 and 6.5, respectively) were determined for all compounds. The experimental study revealed a large diversity in slope, from -0.5 (celiprolol) to -8.6 (hydralazine) in the linear pH-dependent solubility interval, which is in sharp contrast to the slope of -1 assumed by the HH equation. In addition, a large variation in the range of solubility between the completely uncharged and completely charged drug species was observed. The range for disopyramide was only 1.1 log units, whereas that for amiodarone was greater than 6.3 log units, pointing at the compound specific response to counter-ion effects. In conclusion, the investigated cationic drugs displayed compound specific pH-dependent solubility profiles, indicating that that the HH equation in many cases will only give rough estimations of the pH-dependent solubility of drugs in divalent buffer systems.