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Objectives The current study aims to determine the effect of physicochemical descriptor selection on models of polydimethylsiloxane permeation. Methods A total of 2942 descriptors were calculated for a data set of 77 chemicals. Data were processed to remove redundancy, single values, imbalanced and highly correlated data, yielding 1363 relevant descriptors. For four independent test sets, feature selection methods were applied and modelled via a variety of Machine Learning methods. Key findings Two sets of molecular descriptors which can provide improved predictions, compared to existing models, have been identified. Best permeation predictions were found with Gaussian Process methods. The molecular descriptors describe lipophilicity, partial charge and hydrogen bonding as key determinants of PDMS permeation. Conclusions This study highlights important considerations in the development of relevant models and in the construction and use of the data sets used in such studies, particularly that highly correlated descriptors should be removed from data sets. Predictive models are improved by the methodology adopted in this study, notably the systematic evaluation of descriptors, rather than simply using any and all available descriptors, often based empirically on in vitro experiments. Such findings also have clear relevance to a number of other fields.

There is increasing concern that infants and children may be at increased risk of neurological effects of pyrethroids, the most widely used class of insecticide. The objectives of this investigation were to (1) characterize the dose-dependent toxicokinetics (TK) of deltamethrin (DLM) for exposures ranging from environmentally relevant to acutely toxic; (2) determine the influence of an aqueous versus oil vehicle on oral absorption and bioavailability; and (3) determine whether DLM exhibits low-dose, age-equivalent internal dosimetry. Serial arterial plasma samples were obtained for 72 h from adult, male Sprague Dawley rats given 0.05-5.0 mg DLM/kg as an oral bolus in corn oil (CO). DLM exhibited linear, absorption rate-limited TK. Increases in maximum plasma concentration (Cmax) and AUC∘∞ were directly proportional to the dose. Oral bioavailability was quite limited. The vehicle and its volume had modest effect on the rate and extent of systemic absorption in adult rats. Postnatal day (PND) 15, 21, and 90 (adult) rats received 0.10, 0.25, or 0.50 mg DLM/kg orally in CO and were sacrificed periodically for plasma, brain, and liver collection. Age-dependent differences between PND 15 and 90 plasma Cmax and AUC∘24 values progressively diminished as the dose decreased, but there was a lack of low dose age equivalence in these brain and liver dosimeters. Other maturational factors may account for the lack of the low-dose age equivalence in brain and liver. This investigation provides support for the premise that the relatively low metabolic capacity of immature subjects may be adequate to effectively eliminate trace amounts of DLM and other pyrethroids from the plasma.

A sensitive method for the simultaneous determination of cis-permethrin (cis-PERM) and trans-permethrin (trans-PERM) in small volumes (100μL) of rat plasma and brain homogenate was developed, using a liquid-liquid extraction for sample preparation and gas chromatography-negative chemical ionization mass spectrometry (GCNCI-MS) for detection. Quantitation of trace levels of the insecticide in small volumes of biological samples is essential to support toxicokinetic studies in small animals. There are currently no validated methods in the literature for determining cis-PERM and trans- PERM in volumes as low as 100μL of rat plasma or brain homogenate. The method provided a linear range of 0.2-150.0ng/mL for analytes in both matrices. The intra- and inter-batch precision (as% relative standard deviation, RSD) and accuracy (as relative error, RE) of the method were better than 20% at the limit of quantitation and better than 15% across the remaining linear range. The validated method was applied in a toxicokinetic study in adult rats with oral dosing of 10mg/kg (cis-PERM) and 100mg/kg (trans-PERM) in corn oil. cis-PERM and trans- PERM were monitored in rat plasma and brain tissue samples for 6h following dosing, and both analytes were detected in all plasma and brain samples.

The current study aims to determine the effect of physicochemical descriptor selection on models of polydimethylsiloxane permeation.A total of 2942 descriptors were calculated for a data set of 77 chemicals. Data were processed to remove redundancy, single values, imbalanced and highly correlated data, yielding 1363 relevant descriptors. For four independent test sets, feature selection methods were applied and modelled via a variety of Machine Learning methods.Two sets of molecular descriptors which can provide improved predictions, compared to existing models, have been identified. Best permeation predictions were found with Gaussian Process methods. The molecular descriptors describe lipophilicity, partial charge and hydrogen bonding as key determinants of PDMS permeation.This study highlights important considerations in the development of relevant models and in the construction and use of the data sets used in such studies, particularly that highly correlated descriptors should be removed from data sets. Predictive models are improved by the methodology adopted in this study, notably the systematic evaluation of descriptors, rather than simply using any and all available descriptors, often based empirically on in vitro experiments. Such findings also have clear relevance to a number of other fields.

Dimethyl sulfate (DMS) and monomethyl sulfate (MMS) are potential genotoxic impurities created during synthesis of some active pharmaceutical ingredients. While there are a few methods to determine the genotoxic compound DMS, the determination of MMS has not been reported. Novel and sensitive methods to rapidly, simply and efficiently quantify both MMS and DMS impurities in API-salts to determine if patients could potentially meet the threshold of toxicological concern (TTC 1.5 μg per day) were developed and validated according to ICH guidelines. The extremely polar and charged analyte MMS was determined using LC-MS/MS based on reversed-phase ion-pair chromatography with no sample extraction required, and a 5 minute method run time. DMS was determined using liquid–liquid extraction using MTBE and analysed by GC-MS with a 6 minute method run time. These methods provide good recovery, accuracy, and precision over a wide concentration range (2 to 64 μg mL−1 for MMS and 0.1 to 20 μg mL−1 for DMS), which adequately cover the current threshold of toxicological concern.

Reliable analytical methods are needed for the determination of pyrethroid pesticides residues in biological tissues such as whole blood and plasma, meat, eggs, milk, brain, liver, and adipose tissue for monitoring of levels in livestock and for human risk assessment. A review of the current literature is given, with consideration to extraction techniques, sample preparation, and chromatographic approaches including both conventional and new technologies.

RATIONALE Transfluthrin is a relatively non-toxic rapid-acting synthetic pyrethroid insecticide. It is widely used in household and hygiene products. A sensitive and accurate bioanalytical method is required for quantification of its concentration in plasma and its potential target organ, the brain for studies to assess its health effects and toxicokinetics in mammals. METHODS The samples were prepared by liquid-liquid extraction. Gas chromatography mass spectrometry (GC/MS) analysis was performed for the determination of transfluthrin in biological samples with an overall method run time of 15 min. Transfluthrin was quantified using selected-ion monitoring (SIM) in the negative chemical ionization (NCI) mode. Chromatographic separation was achieved using a Zebron® ZB5-MS GC column operating with 1 mL/min constant flow helium. cis-Permethrin was used as the internal standard. RESULTS The method was validated to be precise and accurate within the linear range of 1.0 - 400.0 ng/mL in plasma and 4.0 – 400.0 ng/mL in brain homogenate, based on a 100 μL sample volume for both matrices. This method was applied to samples following administration of a 10 mg/kg oral dose to male adult rats. The plasma concentrations were observed to be 11.70 ± 5.69 ng/mL and brain concentrations 12.09 ± 3.15 ng/g when measured 2 h post-dose. CONCLUSIONS A rapid GC/NCI-MS method was demonstrated to be sensitive, specific, precise and accurate for the quantification of transfluthrin in rat plasma and brain. The optimized method was successfully used to quantify the rat plasma and brain concentrations of transfluthrin 2 h after the oral dosing of Sprague-Dawley rats.

The polyunsaturated fatty acids (PUFA) arachidonic acid (AA, n-6) and eicosapentaenoic acid (EPA, n-3) are precursors of eicosanoids and other lipid mediators which have critical roles in inflammation. The mediators formed from the different PUFA have different potencies. We hypothesised that metabolic changes associated with colonic mucosal inflammation would modify the bioavailability of the eicosanoid precursors AA and EPA.Colonic mucosa biopsies were obtained from patients with ulcerative colitis and from matched controls. Inflammation was graded endoscopically and histologically. Esterified and non-esterified fatty acids were determined within the biopsies using gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry, respectively.Biopsy samples were collected from 69 UC patients (54 providing both inflamed and non-inflamed mucosa) and 69 controls. Inflamed mucosa had higher AA (p0.001) and lower EPA (p0.010) contents and a higher AA:EPA ratio (p0.001). Inflamed mucosa also had higher docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA) and lower linoleic acid (LA) and α-linolenic acid (α-LNA) contents (all p0.001), compared to non-inflamed and controls. There were significant correlations between severity of inflammation and contents of AA, DPA and DHA (positive correlations) and of LA, α-LNA and EPA (negative correlations).Higher AA, AA:EPA ratio, DPA and DHA and lower LA, α-LNA and EPA are seen in inflamed mucosa in UC and correlate with severity of inflammation. This suggests an alteration in fatty acid metabolism in the inflamed gut mucosa, which may offer novel targets for intervention and should be considered if nutritional strategies are used.

Permethrin, the most widely used household insecticide in the United States, is marketed as a mixture of its cis (CIS) and trans (TRANS) isomers. The major objective of this investigation is to develop and utilize a reliable approach to determine in vivo partition coefficients (PCs) for CIS and TRANS in immature and adult Sprague-Dawley rats. Adult, postnatal day (PND) 21, and PND 15 rats were infused with environmentally relevant concentrations of CIS or TRANS via a subcutaneous osmotic pump for 48 or 72 h. The adult and PND 21 rats also received an oral loading dose. Systemic steady-state or equilibrium was attained in each age group within 72 h of the protocol. CIS and TRANS were both distributed to tissues according to their neutral lipid content, with adipose tissue exhibiting much higher tissue:plasma PCs than skeletal muscle, liver, or brain. Liver:plasma and brain:plasma PCs were consistently at or lower than unity. Tissue:plasma PCs were generally higher for CIS than for TRANS, although the isomers are of comparable lipophilicity. Significantly higher blood levels of CIS apparently saturate plasma binding, resulting in greater tissue deposition of the isomer. CIS and TRANS tissue:plasma PCs were found to be inversely related to the rats’ age, although TRANS brain:plasma PCs were comparable in immature and mature animals. These data support the conclusion that age-dependent partitioning is an important determinant of the pharmacokinetics of permethrin. Such partitioning could influence the risk assessment of these insecticides in infants and children when incorporated into physiologically based pharmacokinetic models.

An improved bioanalytical method to determine pyrethroids from small-volume (300 μL) rat liver and muscle homogenates was developed, validated, and applied to small-animal studies. The method used dispersive SPE (d-SPE) to clean the samples, and GC negative chemical ion MS (GC-NCI-MS) to analyze the samples. High-quality trace analysis of pyrethroids in biological samples was necessary to assess the health risk of environmentally encountered levels. Currently used highly sensitive methods to measure pyrethroids have focused on large-volume samples related to environmental exposure (water, soil, food products) or urine; however, there are no validated methods for quantifying this class of compounds in small-volume rat liver and muscle tissue homogenates. Individual rat tissue homogenate samples (300 μL) were prepared by protein precipitation using hexane-saturated acetonitrile. The samples were mixed on a vortex mixer and decanted into a d-SPE tube containing octadecylsilyl (C18) and primary secondary amine (PSA) sorbents and magnesium sulfate. The samples were centrifuged before evaporation to dryness. Pyrethroids were extracted and reconstituted from the residue using toluene in advance of injection into an Agilent Model 6890N gas chromatograph equipped with a Model 5973 quadrupole mass analyzer. Samples were ionized via electron capture in the negative ion mode using methane as a chemical ionization gas. Six qualifying ions were monitored using selected-ion monitoring for quantitation and verification of the analyte. Cis-permethrin was used as the internal standard. Method linearity was from 1 to 500 ng/mL for muscle and liver homogenates. The inter- and intraday precision and accuracy of the method were better than 20% at the lower LOQ and better than 15% over the remainder of the linear range. The method was used to elucidate tissue time-courses of deltamethrin (DLM) disposition following oral dosing of rats with 1 to 5 mg/kg in corn oil. DLM was monitored in rat tissue samples ≤24 h following dosing. Sample cleanup with d-SPE provided more selective chromatography than previous analytical methods.

Objectives To determine the metabolism of captopril n-carboxyl derivatives and how this may impact on their use as transdermal prodrugs. The pharmacological activity of the ester derivatives was also characterised in order to compare the angiotensin converting enzyme inhibitory potency of the derivatives compared with the parent drug, captopril. Methods The metabolism rates of the ester derivatives were determined in vitro (using porcine liver esterase and porcine ear skin) and in silico (using molecular modelling to investigate the potential to predict metabolism). Key findings Relatively slow pseudo first-order metabolism of the prodrugs was observed, with the ethyl ester displaying the highest rate of metabolism. A strong relationship was established between in-vitro methods, while in-silico methods support the use of in-vitro methods and highlight the potential of in-silico techniques to predict metabolism. All the prodrugs behaved as angiotensin converting enzyme inhibitors, with the methyl ester displaying optimum inhibition. Conclusions In-vitro porcine liver esterase metabolism rates inform in-vitro skin rates well, and in-silico interaction energies relate well to both. Thus, in-silico methods may be developed that include interaction energies to predict metabolism rates.

Reliable analytical methods are needed for the determination of pyrethroid pesticides residues in biological tissues such as whole blood and plasma, meat, eggs, milk, brain, liver, and adipose tissue for monitoring of levels in livestock and for human risk assessment. A review of the current literature is given, with consideration to extraction techniques, sample preparation, and chromatographic approaches including both conventional and new technologies.

Most drugs are designed primarily for oral administration, but the activity and stability profiles desirable for this route often make them unsuitable for transdermal delivery. We were therefore interested in designing analogues of captopril, a model drug with poor percutaneous penetration, for which the sustained steady-state blood plasma level associated with transdermal delivery (and which is unattainable orally) would be particularly beneficial. Quantitative structure—permeability relationships (QSPRs) predicted that ester and thiol prodrug derivatives of captopril would have lower maximal transdermal flux (Jm) than the parent drug, since the increases in permeability coefficient (kp) of prodrugs would be outweighed by the reductions in aqueous solubility. Therefore, the aim of this study was to synthesize a series of prodrugs of captopril and to determine if a QSPR model could be used to design therapeutically viable prodrugs. Molecules with the highest predicted kp values were synthesized and characterized, and Jm measured in Franz diffusion cells from saturated aqueous donor across porcine skin (fresh and frozen). In-vitro metabolism was also measured. Captopril and the prodrugs crossed the skin relatively freely, with Jm being highest for ethyl to butyl esters. Substantial first-order metabolism of the prodrugs was observed, suggesting that their enhanced percutaneous absorption was complemented by their metabolic performance. The results suggested that QSPR models provided excellent enhancements in drug delivery. This was not seen at higher lipophilicities, suggesting that issues of solubility need to be considered in conjunction with any such use of a QSPR model.

In the development of bioadhesive patch devices for percutaneous local anesthesia, the tensile properties of the films produced after the casting of the gel intermediates is of key importance to the clinical compliance of the product, and its effective delivery of the local anesthetic agent. A range of bioadhesive patches were formulated and their mechanical and in vitro permeation properties determined. Altering formulation significantly altered the mechanical properties of films. The tensile properties of the films could be modified to allow concomitant benefits in the mechanical and drug permeation properties of the films, ensuring that patches not only exerted clinically beneficial effects, but are also mechanically robust. Tetracaine was found to plasticize films and while this effect was weak, it was significant both statistically and potentially also in the effect it has on the clinical use of these devices. Drug release from tetracaine patches demonstrate the same trends as found previously across polydimethylsiloxane films. By altering the formulation of the patch device, the drug release from the device to the skin is readily and accurately controlled, and was not solely a function of the stratum corneum barrier properties but additionally of the formulation.

This chapter deals with an important aspect of skin permeability which generally sits outside the field of predictive model development—finite-dosing and non-steady-state modelling. This is an area generally but not exclusively associated with the occupational risk exposure and industrial chemical fields. It relates to “real” systems where the controls and conditions described in Chap. 2, and used as the basis for a number of the experiments these models rely on, do not apply. Such systems are difficult and challenging to work with, and this chapter discusses approaches to solving these problems, including the formulation-focused work on finite-dose systems by Riviere which include blends of descriptors, including those which highlight solubility and formulation issues, rather than those which describe the physicochemical properties of the penetrants.

This chapter is a comprehensive critique of algorithms for percutaneous absorption. Using the relationship in a model between its input and output, it critiques the nature, development applicability and use of these models in terms of the wider understanding of their context and appropriate application. While highlighting the benefits of these models—which are mostly related to mechanistic insight and predictive ability—the misuse of models is discussed; this includes how nonlinear models may be prone to over-fitting and adopting redundant descriptors in model development, while also addressing the limitations of linear models, particularly highlighting situations where such models clearly fail to reflect experimental observations. Overall, this chapter seeks to find common ground between these different methods and highlights benefits and pitfalls in their use, which should always be anchored in the experimental situation to which the model is applied and which should always understand how—and from which sources—a model has been developed.

This chapter describes the structure of the skin and its stratified nature, emphasising and focusing on the skin’s main barrier to permeation—the stratum corneum—and how its structure and its nature, compared to underlying layers, results in a substantial barrier to both the ingress of exogenous materials and the egress of materials such as water. Methods of transport across the skin barrier and underlying tissues are reviewed, including the relative contributions of the transappendageal, intercellular and intracellular pathways to the overall absorption process, and how recent understandings of the skin barrier are still shaping our knowledge of this barrier. Strategies to enhance absorption are discussed: this will consider, for example, classical formulation methods, the use of solvents to enhance absorption, chemical penetration enhancers, and physical methods of enhancement (including iontophoresis, sonophoresis and the use of prodrug strategies to enhance absorption). This is described in a manner appropriate for contextualisation to the wider themes of this book.

This chapter describes the advances made in methodological aspects of modelling skin permeability by considering artificial intelligence, fuzzy logic and advanced Machine Learning methods and how they have been applied to skin absorption. It reviews the often-stunted contribution to the field of these methods and describes the advantages such methods have produced in recent years. In addition, the chapter also considers problems with these methods, particularly the lack of use in the skin permeability field due to the need for specific computational expertise that is not normally associated with the development of quantitative structure–permeability models, and discusses how such lack of widespread use can be tackled. In addition, as this chapter describes models that often fall into the “black box” category and do not therefore present a readily usable algorithm, an explicit output methods used to discern mechanistic aspects of the skin permeability process are discussed. These include feature selection methods, which have been applied to skin permeability and which have shown the non-independence and interrelationship of key descriptors on each other and that the need for an algorithm with discrete expressions may be of limited value.

This chapter briefly summaries the underlying mathematics of skin absorption and then focuses on early models of skin absorption. It describes the early studies in understanding the pharmacokinetics of skin absorption and the mathematical basis for skin absorption. The early development of key mathematical relationships between permeability and molecular properties is discussed. In particular, emphasis is given to the work of Flynn, El Tayar, and Potts and Guy in developing—and quantifying via algorithms—the mechanistic understanding of the process of skin absorption.

A significant number of studies have explored the use of artificial membranes, such as polydimethylsiloxane (PDMS, Silastic®) as alternatives to mammalian skin. While clearly limited in their ability to replicate the complexity of mammalian skin, these membranes have found a significant role in skin permeability studies as their consistency and ease of use have found an important role in early-stage assessment of percutaneous absorption and in topical formulation development. Thus, this chapter focuses on the development of mathematical models for permeability across such membranes and discusses them in the context of mammalian skin permeability in terms of mechanistic value through similarity, or otherwise, to mammalian skin and predictive ability.

This chapter considers those approaches to modelling skin absorption that sit outside the “mainstream” of models based on the approach of Flynn and Potts and Guy and which are often presented as isolated or single diversions into novel aspects of skin permeation. While understanding that the underlying methodology in such studies does not generally change, this chapter describes models developed for non-human species, including rabbit and guinea pig, and how variations of experimental protocols (such as pretreatment and temperature) influence the output of models. It also examines the influence of formulation/vehicles effects on skin absorption, something which is not often considered in other models. Finally, the flux-based models of Roberts are considered in the context of their mechanistic insight and how they can be used to improve the real-world application of algorithms of skin permeability.

This chapter summarises the preceding sections of the book and proposes a series of recommendations for model development and use. These recommendations are based on proposals more widely described in the field of quantitative structure–activity relationships (QSARs) by Cronin, Dearden and others. Implicitly, they suggest that researchers modelling skin permeability should look outside their own field and construct models in a way that is consistent with researchers in other fields. Key findings in the field are discussed, including the significance for data quality of Chilcott’s multicentre validation study and Johnson’s work on the consistency of steroid permeability data, how differing experimental protocols and anomalous data may influence model outputs and the application of predictive software in the generation of physicochemical data. Thus, a series of recommendations on the quality and use of source data, methodological approaches and model transparency are proposed.

Following the pioneering work in this field by El Tayar, Flynn and Potts and Guy—described in Chap. 3—this chapter describes the work that followed and which saw, in the 1990s onwards, a large expansion of interest in this field. This lead to the proliferation of a number of new QSAR models, most of which involved similar methodological approaches and the use of the same data—often as specific subsets focusing on particular classes of chemicals, such as congeneric series or non-electrolytes. In parallel with this, other researchers—notably, Roberts, Hadgraft and Watkinson—proposed through a series of studies an enhanced mechanistic understanding of the skin permeability process and which offers a direct link to the first work in this field through its mechanistic insights when a large number of other studies were simply developing quantitative expressions of limited applicability. Issues of data quality are also discussed in the context of studies by Johnson and Cronin, in particular. This chapter also discusses the implications to these analyses, particularly in terms of experimental design, data set size and consistency, relevance of models to a particular “molecular space” and ultimately, the need for new, consistent sources of data from which to construct models.

The aim of this chapter is to introduce the physical laboratory-based processes that lead to the generation of skin absorption data—the data used to construct mathematical models which describe the skin permeation process. This chapter describes experimental procedures for the production of in vitro skin permeability data and does so in the context of how this data are used in mathematical modelling studies. Experimental procedures, including tape stripping, the use of static or flow-through diffusion cells and the influence of experimental temperature on diffusion, are discussed. The nature of the membranes used for in vitro studies will also be discussed, both experimentally and in the development of mathematical models. This includes the use of artificial membranes, particularly the rationale for their use and how researchers have attempted to correlate absorption across such membranes with absorption across mammalian skin.

Predicting the rate of percutaneous absorption across mammalian and artificial membranes is a complex problem. In previous studies, prediction and accuracy are approached using different machine learning models. Results show that Gaussian processes provided the best result, based on a range of statistical measures. In general the ultimate aim of these machine learning experiments is to try to understand, analyze and predict the percutaneous absorption of drugs across human skin. One way to do this is to select the best set of chemical descriptors and the dataset of synthetic (Polydimethyl siloxane, PDMS) membranes, containing so many descriptors, is considered a suitable dataset to use in this study. Hence, one of the main purposes of the study is to use feature selection methods to select the molecular properties that exert the most important influence on percutaneous absorption across PDMS membranes, in the hope that this will better inform studies on human skin.

Polydimethylsiloxane (PDMS) silicone membranes, such as Silastic®, have been used widely in place of mammalian tissue in the determination of percutaneous absorption. While many experiments have shown correlations between the permeability across both membranes, Moss et al. demonstrated in a systematic study that PDMS membranes tend to exhibit greater permeability than mammalian skin, and that the relationship between permeability across both membranes was not found when the lipophilicity of the penetrant was greater than 3. Further, it was shown previously that when five commonly used physicochemical descriptors were applied to human, pig and rodent membranes they cannot represent the main characteristics of the PDMS dataset when using Gaussian Process (GP) regression to predict skin permeability. However, the previous study in which this process was modelled employed a small dataset (n=19, as part of the wider aims of that work to investigate the effect of dataset construction on model quality).

Quantification of the pyrethroid deltamethrin (DLM) in small (100 μL) biological samples from rodents is essential for toxicokinetic studies of trace levels of the insecticide in foods. Such empirical kinetic data are necessary for construction of valid physiologically-based toxicokinetic models. There are no validated methods in the literature for determining deltamethrin in 100 μL plasma and brain samples. Plasma and brain samples were stabilized using sodium fluoride as an esterase inhibitor, and the DLM was extracted by protein precipitation using acetonitrile and phosphoric acid. The samples were vortexed, centrifuged, evaporated to dryness, and reconstituted in toluene prior to injection into a gas chromatograph equipped with a quadrupole mass analyzer. Samples were ionized via electron capture in the negative ion mode using methane, and the molecular ion and fragment ions of DLM were monitored using Selected-Ion Monitoring (SIM) for quantitation and verification of the analyte. Cis-permethrin was used as the internal standard for the method, which was validated according to current US FDA guidelines. Linearity was determined between 0.3 and 1,000 ng/mL, with a limit of detection of 150 pg/mL. The intra- and inter-batch variation for precision (as % relative standard deviation, RSD) and accuracy (as % bias) of the method were better than 20% at the limit of quantitation and better than 15% across the remaining linear range (n=18), with recoveries of 113% and 68% for plasma and brain respectively. Benchtop stability, autosampler stability, and freeze/thaw stability studies of the method (over a 3-day freeze/thaw cycle) were found to be within the acceptance criteria of 20% RSD and bias. This optimized method was applied to the quantitation of DLM in plasma and brain homogenate samples obtained up to 12h after oral dosing of Sprague-Dawley rats with 1mg DLM/kg body weight.

The ethyl ester of captopril has been shown to exhibit enhanced permeation across human skin compared to the parent drug. A drug-in-adhesive patch formulation of a captopril ethyl ester was therefore developed for optimum drug release.A wide range of transdermal patches were prepared using two commercially available bioadhesive polymers. Investigational screening was conducted on the patches using microscopy, texture profile analysis, and infrared spectroscopy. Drug release profiles of suitable patches were obtained using both polydimethylsiloxane (Silastic) and porcine skin in vitro.Diffusion results across Silastic showed a gradual plateau in flux with increased drug loading that may be attributable to intramolecular interactions while flux across porcine skin was seen to increase with increasing patch thickness and attained a therapeutic level.This study demonstrated that adhesion and drug loading are significant factors in optimizing a topical patch formulation for the delivery of a captopril prodrug.

To determine the metabolism of captopril n-carboxyl derivatives and how this may impact on their use as transdermal prodrugs. The pharmacological activity of the ester derivatives was also characterised in order to compare the angiotensin converting enzyme inhibitory potency of the derivatives compared with the parent drug, captopril.The metabolism rates of the ester derivatives were determined in vitro (using porcine liver esterase and porcine ear skin) and in silico (using molecular modelling to investigate the potential to predict metabolism).Relatively slow pseudo first-order metabolism of the prodrugs was observed, with the ethyl ester displaying the highest rate of metabolism. A strong relationship was established between in-vitro methods, while in-silico methods support the use of in-vitro methods and highlight the potential of in-silico techniques to predict metabolism. All the prodrugs behaved as angiotensin converting enzyme inhibitors, with the methyl ester displaying optimum inhibition.In-vitro porcine liver esterase metabolism rates inform in-vitro skin rates well, and in-silico interaction energies relate well to both. Thus, in-silico methods may be developed that include interaction energies to predict metabolism rates.

A C2/C2'-exo-unsaturated pyrrolo[2,1-c][1,4]benzodiazepine (PBD) dimer 4b (DRG-16) with a C8-O(CH2)nO-C8' diether linkage (n = 5) has been synthesized that shows markedly superior in vitro cytotoxic potency (e.g., >3400-fold in IGROV1 ovarian cells) and interstrand DNA cross-linking reactivity (>10-fold) compared to the shorter homologue 4a (SJG-136; n = 3). In contrast, for the C-ring unsubstituted series, the corresponding n = 5 dimer (3c) is generally less cytotoxic and has a lower interstrand cross-linking reactivity compared to its shorter n = 3 homologue (3a). Dimer 4b cross-links DNA with >10-fold efficiency compared to 4a, and also inhibits the activity of the restriction endonuclease BamH1 more efficiently than either 3a or 4a. The C2-exo-unsaturated PBD dimers 4a,b are not only more effective than their C-ring saturated counterparts in terms of induced DeltaTm shift, but they also exert this effect more rapidly. Thus, while 3a and 3c exert 68 and 35% of their maximum effect immediately upon interaction with DNA, this level increases to 76 and 97% for 4a and 4b, respectively. Molecular modeling shows a rank order of 4b (n = 5) > 4a (n = 3) > 3a (n = 3) > 3c (n = 5) in terms of binding energy toward duplexes containing embedded target 5'-GAT(1-2)C cross-link sequences, reflecting the superior fit of the C2-exo-unsaturated rather than saturated C-rings of the PBD dimers. A novel synthesis of core synthetic building blocks for PBD dimers via stepwise Mitsunobu reaction and nitration with Cu(NO3)2 is also reported.

Introduction The polyunsaturated fatty acids (PUFA) arachidonic acid (AA), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA) are generated from dietary essential fatty acids linoleic acid (LA) and α-linolenic acid (αLNA) and direct dietary intake. AA and EPA are substrates for eicosanoid inflammatory mediators that may have critical roles in immunomodulation in Ulcerative Colitis (UC). Dietary supplementation studies alter the availability of specific PUFA (eg, EPA), but clinical studies have been disappointing leading to the hypothesis that the PUFA biosynthetic pathway in inflamed tissue may be altered. This study evaluated PUFA bioavailability in inflamed and uninflamed mucosa from UC patients and compared to matched controls. Methods Ethical approval was obtained. Patients were prospectively recruited from outpatients9 clinics. Mucosal biopsies at flexible sigmoidoscopy (FS) were taken from active UC patients within inflamed (active) and endoscopically normal proximal mucosa (internal control). Age-sex matched patients undergoing FS for IBS or similar presentations were compared (external controls). Mucosal samples were saponified, deuterated internal standards added, lipids hydrolysed and fatty acids derivatised prior to liquid-liquid extraction into heptane. PUFA were quantified by gas chromatography mass spectrometry. Data was expressed as percentage mass abundance and compared using Wilcoxon signed rank pair analysis for non-parametric data. Results 69 active UC patients (54 paired normal/inflamed mucosa) and 69 controls were compared. No biologically significant differences were noted between endoscopically normal mucosa from UC patients and external controls other than DPA (p Conclusion PUFA bioavailability within normal mucosa in UC patients is not significantly different from matched controls; however, inflamed mucosa demonstrates significant differences in the bioavailability of PUFA with a reduction in LA and αLNA and a divergent change in AA and EPA leading to a significant increase in the AA/EPA ratio. These findings suggest alteration of the fatty acid biosynthetic pathway in inflamed tissue and may suggest that alternative therapeutic strategies are required to modify the eicosanoid profile in UC.

Introduction Ulcerative colitis (UC) is a colonic inflammatory disorder of unconfirmed aetiology. Eicosanoids, inflammatory mediators involved in UC pathogenesis, are enzymatically converted from dietary polyunsaturated fatty acids (PUFA), arachidonic acid (AA) and eicosapentaenoic acid (EPA), themselves competitive substrates also generated via a fatty acid (FA) biosynthetic cascade. Dietary studies using fish oil-derived EPA have been disappointing in UC; we hypothesised that the PUFA biosynthetic pathway in inflamed tissue is altered. This study evaluated PUFA profile in inflamed and non-inflamed mucosa from UC patients and compared to matched controls. Methods Ethical approval was obtained. Patients were prospectively recruited from outpatients9 clinics. Mucosal biopsies at flexible sigmoidoscopy (FS) were taken from UC patients within inflamed and normal proximal mucosa. Age-sex matched control patients undergoing FS for functional symptoms were compared. Inflammation was scored endoscopically and histologically. Membrane bound FA (MBFA): Biopsies were spiked with deuterated internal standard, followed by liquid-liquid extraction and quantitative gas chromatography mass spectrometry (MS). Free Fatty Acid (FFA): Biopsies were homogenised, followed by solid phase extraction and liquid chromatography orbitrap MS. Data were expressed as percentage abundance. Dietary fatty acid analysis was undertaken. Wilcoxon signed rank pair and Spearman9s correlation analysis were employed. Results 69 active UC patients (54 paired normal/inflamed mucosa) and 69 controls were compared. No biologically significant differences were noted between endoscopically normal mucosa from UC patients and controls other than DPA (p Conclusion Mucosal PUFA bioavailability is altered in active UC, with significant elevation of AA and reduction of LA, αLNA and EPA. This suggests modification of the FA biosynthetic pathway with elevated delivery of AA as a precursor of pro-inflammatory eicosanoids in active UC. These findings may explain the lack of efficacy of supplemental fish oil and suggests new alternative therapeutic targets. Competing interests None declared.