An interesting relationship between drug absorption and melting point

Modeling of Effectiveness of N3-Substituted Amidrazone Derivatives as Potential Agents against Gram-Positive Bacteria

Prediction of the antibacterial activity of new chemical compounds is an important task, due to the growing problem of bacterial drug resistance. Generalized linear models (GLMs) were created using 85 amidrazone derivatives based on the results of antimicrobial activity tests, determined as the minimum inhibitory concentration (MIC) against Gram-positive bacteria: Staphylococcus aureus, Enterococcus faecalis, Micrococcus luteus, Nocardia corallina, and Mycobacterium smegmatis. For the analysis of compounds characterized by experimentally measured MIC values, we included physicochemical properties (e.g., molecular weight, number of hydrogen donors and acceptors, topological polar surface area, compound percentages of carbon, nitrogen, and oxygen, melting points, and lipophilicity) as potential predictors. The presence of R1 and R2 substituents, as well as interactions between melting temperature and R1 or R2 substituents, were also considered. The set of potential predictors also included possible biological effects (e.g., antibacterial, antituberculotic) of tested compounds calculated with the PASS (Prediction of Activity Spectra for Substances) program. Using GLMs with least absolute shrinkage and selection (LASSO), least-angle regression, and stepwise selection, statistically significant models with the optimal value of the adjusted determination coefficient and of seven fit criteria were chosen, e.g., Akaike's information criterion. The most often selected variables were as follows: molecular weight, PASS_antieczematic, PASS_anti-inflam, squared melting temperature, PASS_antitumor, and experimental lipophilicity. Additionally, relevant to the bacterial strain, the interactions between melting temperature and R1 or R2 substituents were selected, indicating that the relationship between MIC and melting temperature depends on the type of R1 or R2 substituent.

The synthesis and characterization of a series of cocrystals of an isoniazid derivative with butan-2-one and propan-2-one

Four cocrystals containing N'-(butan-2-ylidene)pyridine-4-carbohydrazide (izbt) and one cocrystal containing N'-isopropylideneisonicotinohydrazide (izact) were synthesized by reacting isoniazid with either butan-2-one (for the former) or acetone (for the latter). The coformers used to synthesize the izbt cocrystals were 2,4-dihydroxybenzoic acid, 2,5-dihydroxybenzoic acid, 2-chloro-4-nitrobenzoic acid and 1-naphthoic acid. 1-Naphthoic acid was also used with izact to form a cocrystal. The 1:1 cocrystals are: N'-(butan-2-ylidene)pyridine-4-carbohydrazide-1-naphthoic acid (izbt-1nta), C10H13N3O·C11H8O2, N'-(butan-2-ylidene)pyridine-4-carbohydrazide-2,4-dihydroxybenzoic acid (izbt-2,4-dhba), C10H13N3O·C7H6O4, N'-(propan-2-ylidene)pyridine-4-carbohydrazide-1-naphthoic acid (izact-1nta), C9H11N3O·C11H8O2, N'-(butan-2-ylidene)pyridine-4-carbohydrazide-2-chloro-4-nitrobenzoic acid (izbt-2c4n), C10H13N3O·C7H4ClNO4, and N'-(butan-2-ylidene)pyridine-4-carbohydrazide-2,5-dihydroxybenzoic acid (izbt-2,5-dhba), C10H13N3O·C7H6O4. The cocrystals containing izbt were compared to those containing the same (or similar) coformers with izact that have been reported either here or in the Cambridge Structural Database (CSD). Most of the cocrystals showed different packing despite having the same hydrogen-bonding motifs. The cocrystals were characterized by single-crystal X-ray diffraction (SC-XRD), powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC).

Predicting the Melting Point of Energetic Molecules Using a Learnable Graph Neural Fingerprint Model

Melting point prediction for organic molecules has drawn widespread attention from both academic and industrial communities. In this work, a learnable graph neural fingerprint (GNF) was employed to develop a melting point prediction model using a dataset of over 90,000 organic molecules. The GNF model exhibited a significant advantage, with a mean absolute error (MAE) of 25.0 K, when compared to other featurization methods. Furthermore, by integrating prior knowledge through a customized descriptor set (i.e., CDS) into GNF, the accuracy of the resulting model, GNF_CDS, improved to 24.7 K, surpassing the performance of previously reported models for a wide range of structurally diverse organic compounds. Moreover, the generalizability of the GNF_CDS model was significantly improved with a decreased MAE of 17 K for an independent dataset containing melt-castable energetic molecules. This work clearly demonstrates that prior knowledge is still beneficial for modeling molecular properties despite the powerful learning capability of graph neural networks, especially in specific fields where chemical data are lacking.

Expedient Access to Underexplored Chemical Space: Deoxygenative C(sp3)-C(sp3) Cross-Coupling

Alcohols are commercially abundant and structurally diverse reservoirs of sp3-hybridized chemical space. However, the direct utilization of alcohols in C-C bond-forming cross-couplings remains underexplored. Herein we report an N-heterocyclic carbene (NHC)-mediated deoxygenative alkylation of alcohols and alkyl bromides via nickel-metallaphotoredox catalysis. This C(sp3)-C(sp3) cross-coupling exhibits a broad scope and is capable of forming bonds between two secondary carbon centers, a longstanding challenge in the field. Highly strained three-dimensional systems such as spirocycles, bicycles, and fused rings were excellent substrates, enabling the synthesis of new molecular frameworks. Linkages between pharmacophoric saturated ring systems were readily forged, representing a three-dimensional alternative to traditional biaryl formation. The utility of this cross-coupling technology is highlighted with the expedited synthesis of bioactive molecules.

Isolation, Physicochemical Characterization, and Biological Properties of Inotodiol, the Potent Pharmaceutical Oxysterol from Chaga Mushroom

Inotodiol, an oxysterol found only in Chaga mushroom, has received attention from the pharmaceutical industry due to its strong antioxidant and anti-allergic activities. However, the production of inotodiol is still challenging, and its fundamental properties have yet to be investigated. This study aims to develop an efficient method to produce high-purity inotodiol from Chaga mushroom. Then, pure inotodiol was used to assess its physicochemical properties and biological activities. By optimizing the solvent used for extraction and purification, a new method to produce inotodiol was developed with high purity (>97%) and purification yield (33.6%). Inotodiol exhibited a melting point (192.06 °C) much higher than lanosterol and cholesterol. However, the solubility of inotodiol in organic solvents was notably lower than those of the other two sterols. The difference in the hydroxyl group at C-22 of inotodiol has shown the distinctive physicochemical properties of inotodiol compared with cholesterol and lanosterol. Based on those findings, a nonionic surfactant-based delivery system for inotodiol was developed to improve its bioavailability. The inotodiol microemulsion prepared with 1-2% Tween-80 exhibited homogenous droplets with an acceptable diameter (354 to 217 nm) and encapsulation efficiency (85.6-86.9%). The pharmacokinetic analysis of inotodiol microemulsion in oral administration of 4.5 mg/kg exhibited AUC_0-24h = 341.81 (ng·h/mL), and C_max = 88.05 (ng/mL). Notably, when the dose increased from 4.5 to 8.0 mg/kg, the bioavailability of inotodiol decreased from 41.32% to 33.28%. In a mouse model of sepsis, the serum level of interleukin-6 significantly decreased, and the rectal temperature of mice was recovered in the inotodiol emulsion group, indicating that inotodiol microemulsion is an effective oral delivery method. These results could provide valuable information for applying inotodiol in functional food, cosmetic, and pharmaceutical industries.

Electrospun fibers as carriers for topical drug delivery and release in skin bandages and patches for atopic dermatitis treatment

The skin is a complex layer system and the most important barrier between the environment and the organism. In this review, we describe some widespread skin problems, with a focus on eczema, which are affecting more and more people all over the world. Most of treatment methods for atopic dermatitis (AD) are focused on increasing skin moisture and protecting from bacterial infection and external irritation. Topical and transdermal treatments have specific requirements for drug delivery. Breathability, flexibility, good mechanical properties, biocompatibility, and efficacy are important for the patches used for skin. Up to today, electrospun fibers are mostly used for wound dressing. Their properties, however, meet the requirements for skin patches for the treatment of AD. Active agents can be incorporated into fibers by blending, coaxial or side-by-side electrospinning, and also by physical absorption post-processing. Drug release from the electrospun membranes is affected by drug and polymer properties and the technique used to combine them into the patch. We describe in detail the in vitro release mechanisms, parameters affecting the drug transport, and their kinetics, including theoretical approaches. In addition, we present the current research on skin patch design. This review summarizes the current extensive know-how on electrospun fibers as skin drug delivery systems, while underlining the advantages in their prospective use as patches for atopic dermatitis. This article is categorized under: Implantable Materials and Surgical Technologies > Nanomaterials and Implants Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement Therapeutic Approaches and Drug Discovery > Emerging Technologies.

Targeting highly resisted anticancer drugs through topological descriptors using VIKOR multi-criteria decision analysis

The disease cancer is expanding on high spans in virtually all over the world, and undoubtedly, the research through all the aspects of sciences for each of its perspective is a great cause in reducing its severeness and symptoms. Chemotherapy is itself a cure to cancer as it helps in controlling the formation of cancerous cells but leaving multiple side effects on a human body. In this research work, we targeted 21 anticancer drugs that are in taken by the patients in combinations during chemotherapies. We introduce another branch of mathematics named as OR (Operations Research) linking to the chemical graph theory. Chemical graph theory allows us to generate highly resistant research on any structure via quantitative structure property relationship (QSPR) modeling to explore and develop new compounds for drugs. In this research study, we visualized what else the QSPR could provide when it comes to ranking drugs. We visualized the results obtained for boiling points and enthalpy of vaporizations through QSPR as the values of correlation coefficients and the errors generated under unique QSPR modeling. The implementation of VIKOR provides the best ranking for each of anticancer drugs when keeping in concern the specified properties, and the conclusions from this research work show another path to biologist scientists to create best combinations keeping in concern the study generated from QSPR.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1140/epjp/s13360-022-03469-x.

On the Thermodynamic Thermal Properties of Quercetin and Similar Pharmaceuticals

The thermodynamic properties of pharmaceuticals are of major importance since they are involved in drug design, processing, optimization and modelling. In this study, a long-standing confusion regarding the thermodynamic properties of flavonoids and similar pharmaceuticals is recognized and clarified. As a case study, the thermal behavior of quercetin is examined with various techniques. It is shown that quercetin does not exhibit glass transition nor a melting point, but on the contrary, it does exhibit various thermochemical transitions (structural relaxation occurring simultaneously with decomposition). Inevitably, the physical meaning of the reported experimental values of the thermodynamic properties, such as the heat of fusion and heat capacity, are questioned. The discussion for this behavior is focused on the weakening of the chemical bonds. The interpretations along with the literature data suggest that the thermochemical transition might be exhibited by various flavonoids and other similar pharmaceuticals, and is related to the difficulty in the prediction/modelling of their melting point.

Crystal Structure, Solubility, and Pharmacokinetic Study on a Hesperetin Cocrystal with Piperine as Coformer

Hesperetin (HES) is a key biological active ingredient in citrus peels, and is one of the natural flavonoids that attract the attention of researchers due to its numerous therapeutic bioactivities that have been identified in vitro. As a bioenhancer, piperine (PIP) can effectively improve the absorption of insoluble drugs in vivo. In the present study, a cocrystal of HES and PIP was successfully obtained through solution crystallization. The single-crystal structure was illustrated and comprehensive characterization of the cocrystal was conducted. The cocrystal was formed by two drug molecules at a molar ratio of 1:1, which contained O–H–O hydrogen bonds between the carbonyl and ether oxygen of PIP and the phenolic hydroxyl group of HES. In addition, a solubility experiment was performed on powder cocrystal in simulated gastrointestinal fluid, and the result revealed that the cocrystal improves the dissolution behavior of HES compared with that of the pure substance. Furthermore, HES’s bioavailability in the cocrystal was six times higher than that of pristine drugs. These results may provide an efficient oral formulation for HES.

Finding inhibitors for PCSK9 using computational methods

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is one of the key targets for atherosclerosis drug development as its binding with low-density lipoprotein receptor leads to atherosclerosis. The protein-ligand interaction helps to understand the actual mechanism for the pharmacological action. This research aims to discover the best inhibitory candidates targeting PCSK9. To start with, reported ACE inhibitors were incorporated into pharmacophore designing using PharmaGist to produce pharmacophore models. Selected models were later screened against the ZINC database using ZINCPHARMER to define potential drug candidates that were docked with the target protein to understand their interactions. Molecular docking revealed the top 10 drug candidates against PCSK9, with binding energies ranging from -9.8 kcal·mol^-1 to -8.2 kcal·mol^-1, which were analyzed for their pharmacokinetic properties and oral bioavailability. Some compounds were identified as plant-derived compounds like (S)-canadine, hesperetin or labetalol (an antihypertensive drug). Molecular dynamics results showed that these substances formed stable protein-ligand complexes. (S)-canadine-PCSK9 complex was the most stable with the lowest RMSD. It was concluded that (S)-canadine may act as a potential inhibitor against atherosclerosis for the development of new PCSK9 inhibitory drugs in future in vitro research.

Enantioselective Synthesis and Profiling of Potent, Nonlinear Analogues of Antimalarial Tetraoxanes E209 and N205

Synthetic endoperoxide antimalarials, such as 1,2,4-trioxolanes and 1,2,4,5-tetraoxanes, are promising successors for current front-line antimalarials, semisynthetic artemisinin derivatives. However, limited solubility of second-generation analogues in biological-relevant media represents a barrier in clinical development. We present methodology for the synthesis of nonlinear analogues of second-generation tetraoxane antimalarials E209 and N205 to investigate reduced molecular symmetry on in vitro antimalarial activity and physicochemical properties. While maintaining good antimalarial activity and metabolic stability, head-to-head comparison of linear and nonlinear counterparts showed up to 10-fold improvement in FaSSIF solubility for three of the four analogues studied. Pharmacokinetic studies in rats comparing a selected nonlinear analogue 14a and its parent N205 showed improvement on oral absorption and exposure in vivo with more than double the AUC and a significant increase in oral bioavailability (76% versus 41%). These findings provide support for further in vivo efficacy studies in preclinical animal species.

Transdermal Delivery of Chemotherapeutics: Strategies, Requirements, and Opportunities

Chemotherapeutic drugs are primarily administered to cancer patients via oral or parenteral routes. The use of transdermal drug delivery could potentially be a better alternative to decrease the dose frequency and severity of adverse or toxic effects associated with oral or parenteral administration of chemotherapeutic drugs. The transdermal delivery of drugs has shown to be advantageous for the treatment of highly localized tumors in certain types of breast and skin cancers. In addition, the transdermal route can be used to deliver low-dose chemotherapeutics in a sustained manner. The transdermal route can also be utilized for vaccine design in cancer management, for example, vaccines against cervical cancer. However, the design of transdermal formulations may be challenging in terms of the conjugation chemistry of the molecules and the sustained and reproducible delivery of therapeutically efficacious doses. In this review, we discuss the nano-carrier systems, such as nanoparticles, liposomes, etc., used in recent literature to deliver chemotherapeutic agents. The advantages of transdermal route over oral and parenteral routes for popular chemotherapeutic drugs are summarized. Furthermore, we also discuss a possible in silico approach, Formulating for Efficacy™, to design transdermal formulations that would probably be economical, robust, and more efficacious.

An integrated computational methodology with data-driven machine learning, molecular modeling and PBPK modeling to accelerate solid dispersion formulation design

Drugs in solid dispersion (SD) take advantage of fast and extended dissolution, thus attains a higher bioavailability than the crystal form. However, current development of SD relies on a random large-scale formulation screening method with low efficiency. Current research aims to integrate various computational tools, including machine learning (ML), molecular dynamic (MD) simulation and physiologically based pharmacokinetic (PBPK) modeling, to accelerate the development of SD formulations. Firstly, based on a dataset consisting of 674 dissolution profiles of SD, the random forest algorithm was used to construct a classification model to distinguish two types of dissolution profiles: "spring-and-parachute" and "maintain supersaturation", and a regression model to predict the time-dependent dissolution profiles. Both of the two prediction models showed good prediction performance. Moreover, feature importance was performed to help understand the key information that contributes to the model. After that, the vemurafenib (VEM) SD formulation in previous report was used as an example to validate the models. MD simulation was used to investigate the dissolution behavior of two SD formulations with two polymers (HPMCAS and Eudragit) at the molecular level. The results showed that the HPMCAS-based formulation resulted in faster dissolution than the Eudragit formulation, which agreed with the reported experimental results. Finally, a PBPK model was constructed to accurately predict the human pharmacokinetic profile of the VEM-HPMCAS SD formulation. In conclusion, combined computational tools have been developed to in silico predict formulation composition, in vitro release and in vivo absorption behavior of SD formulations. The integrated computational methodology will significantly facilitate pharmaceutical formulation development than the traditional trial-and-error approach in the laboratory.

Discovery of Roblitinib (FGF401) as a Reversible-Covalent Inhibitor of the Kinase Activity of Fibroblast Growth Factor Receptor 4

FGF19 signaling through the FGFR4/β-klotho receptor complex has been shown to be a key driver of growth and survival in a subset of hepatocellular carcinomas, making selective FGFR4 inhibition an attractive treatment opportunity. A kinome-wide sequence alignment highlighted a poorly conserved cysteine residue within the FGFR4 ATP-binding site at position 552, two positions beyond the gate-keeper residue. Several strategies for targeting this cysteine to identify FGFR4 selective inhibitor starting points are summarized which made use of both rational and unbiased screening approaches. The optimization of a 2-formylquinoline amide hit series is described in which the aldehyde makes a hemithioacetal reversible-covalent interaction with cysteine 552. Key challenges addressed during the optimization are improving the FGFR4 potency, metabolic stability, and solubility leading ultimately to the highly selective first-in-class clinical candidate roblitinib.

Interrelation of thermodynamic sublimation characteristics with crystal structure: adamantane and memantine derivatives of sulfonamide molecular crystals

A number of sulfonamide compounds with adamantane (tricyclo[3.3.1.13,7]decane) and memantine (3,5-dimethyladamantan-1-amine) fragments have been synthesized and characterized.

Novel epidithiodiketopiperazines as anti-viral zinc ejectors of the Feline Immunodeficiency Virus (FIV) nucleocapsid protein as a model for HIV infection

Focused libraries of multi-substituted epidithiodiketopiperazines (ETP) were prepared and evaluated for efficacy of inhibiting the nucleocapsid protein function of the Feline Immunodeficiency Virus (FIV) as a model for HIV. This activity was compared and contrasted to observed toxicity utilising an in-vitro cell culture approach. This resulted in the identification of several promising lead compounds with nanomolar potency in cells with low toxicity and a favorable therapeutic index.

Pharmaceutical Effects of Inhibiting the Soluble Epoxide Hydrolase in Canine Osteoarthritis

Osteoarthritis (OA) is a degenerative joint disease that causes pain and bone deterioration driven by an increase in prostaglandins (PGs) and inflammatory cytokines. Current treatments focus on inhibiting prostaglandin production, a pro-inflammatory lipid metabolite, with NSAID drugs; however, other lipid signaling targets could provide safer and more effective treatment strategies. Epoxides of polyunsaturated fatty acids (PUFAs) are anti-inflammatory lipid mediators that are rapidly metabolized by the soluble epoxide hydrolase (sEH) into corresponding vicinal diols. Interestingly, diol levels are increased in the synovial fluid of humans with OA, warranting further research on the biological role of this lipid pathway in the progression of OA. sEH inhibitors (sEHI) stabilize these biologically active, anti-inflammatory lipid epoxides, resulting in analgesia in both neuropathic, and inflammatory pain conditions. Most experimental studies testing the analgesic effects of sEH inhibitors have used experimental rodent models, which do not completely represent the complex etiology of painful diseases. Here, we tested the efficacy of sEHI in aged dogs with natural arthritis to provide a better representation of the clinical manifestations of pain. Two sEHI were administered orally, once daily for 5 days to dogs with naturally occurring arthritis to assess efficacy and pharmacokinetics. Blinded technicians recorded the behavior of the arthritic dogs based on pre-determined criteria to assess pain and function. After 5 days, EC1728 significantly reduced pain at a dose of 5 mg/kg compared to vehicle controls. Pharmacokinetic evaluation showed concentrations exceeding the enzyme potency in both plasma and synovial fluid. In vitro data showed that epoxyeicosatrienoic acid (EETs), epoxide metabolites of arachidonic acid, decreased inflammatory cytokines, IL-6 and TNF-α, and reduced cytotoxicity in canine chondrocytes challenged with IL1β to simulate an arthritic environment. These results provide the first example of altering lipid epoxides as a therapeutic target for OA potentially acting by protecting chondrocytes from inflammatory induced cytotoxicity. Considering the challenges and high variability of naturally occurring disease in aged dogs, these data provide initial proof of concept justification that inhibiting the sEH is a non-NSAID, non-opioid, disease altering strategy for treating OA, and warrants further investigation.

Intracellular uptake of EGCG-loaded deformable controlled release liposomes for skin cancer

Caucasian population groups have a higher propensity to develop skin cancer, and associated clinical interventions often present substantial financial burden on healthcare services. Conventional treatments are often not suitable for all patient groups as a result of poor efficacy and toxicity profiles. The primary objective of this study was to develop a deformable liposomal formulation, the properties of which being dictated by the surfactant Tween 20, for the dermal cellular delivery of epigallocatechin gallatein (EGCG), a compound possessing antineoplastic properties. The results demonstrated a significant (p ≤ 0.05) decrease in liposome deformability index (74 ± 8 to 37 ± 7) as Tween 20 loading increased from 0 to 10% w/w, indicating an increase in elasticity. EGCG release over 24-h demonstrated Tween 20 incorporation directly increased release from 13.7% ± 1.1% to 94.4% ± 4.9% (for 0 and 10% w/w Tween 20 respectively). Finally, we demonstrated DilC-loaded deformable liposomes were localized intracellularly within human dermal fibroblast and keratinocyte cells within 2 h. Thus, it was evident that deformable liposomes may aid drug penetration into dermal cells and would be useful in developing a controlled-release formulation.

Identification and Optimization of Novel Small c-Abl Kinase Activators Using Fragment and HTS Methodologies

Abelson kinase (c-Abl) is a ubiquitously expressed, nonreceptor tyrosine kinase which plays a key role in cell differentiation and survival. It was hypothesized that transient activation of c-Abl kinase via displacement of the N-terminal autoinhibitory "myristoyl latch", may lead to an increased hematopoietic stem cell differentiation. This would increase the numbers of circulating neutrophils and so be an effective treatment for chemotherapy-induced neutropenia. This paper describes the discovery and optimization of a thiazole series of novel small molecule c-Abl activators, initially identified by a high throughput screening. Subsequently, a scaffold-hop, which exploited the improved physicochemical properties of a dihydropyrazole analogue, identified through fragment screening, delivered potent, soluble, cell-active c-Abl activators, which demonstrated the intracellular activation of c-Abl in vivo.

Humble beginnings with big goals: Small molecule soluble epoxide hydrolase inhibitors for treating CNS disorders

Soluble epoxide hydrolase (sEH) degrades epoxides of fatty acids including epoxyeicosatrienoic acid isomers (EETs), which are produced as metabolites of the cytochrome P450 branch of the arachidonic acid pathway. EETs exert a variety of largely beneficial effects in the context of inflammation and vascular regulation. sEH inhibition is shown to be therapeutic in several cardiovascular and renal disorders, as well as in peripheral analgesia, via the increased availability of anti-inflammatory EETs. The success of sEH inhibitors in peripheral systems suggests their potential in targeting inflammation in the central nervous system (CNS) disorders. Here, we describe the current roles of sEH in the pathology and treatment of CNS disorders such as stroke, traumatic brain injury, Parkinson's disease, epilepsy, cognitive impairment, dementia and depression. In view of the robust anti-inflammatory effects of stem cells, we also outlined the potency of stem cell treatment and sEH inhibitors as a combination therapy for these CNS disorders. This review highlights the gaps in current knowledge about the pathologic and therapeutic roles of sEH in CNS disorders, which should guide future basic science research towards translational and clinical applications of sEH inhibitors for treatment of neurological diseases.

Chemometric Evaluation of THz Spectral Similarity for the Selection of Early Drug Candidates

In this paper we discuss the link between the domain of physical parameters - molecular descriptors of a drug, and terahertz (THz) spectra. We measured the derivatives of the well-known anti-inflammatory drug Piroxicam using THz spectroscopy and employed Principal Component Analysis to build similarity maps in the molecular descriptor and spectral domains. We observed, that the spatial neighborhood on the molecular descriptors map is highly correlated with the spectral neighbourhood within a group of structurally-similar molecules. We built a Partial Least Squares (PLS) predictive model to quantify the relationship between the spectra and the melting point, which can guide the selection of early drug candidates.

On drug-base incompatibilities during extrudate manufacture and fused deposition 3D printing

Aim: 3D printing can be applied for point-of-care personalized treatment. This study aimed to determine the manufacturability and characteristics of 3D printed, drug-loaded implants for alcohol misuse. Materials & methods: Disulfiram was the drug substance used and polylactic acid (PLA) the base material. Implantable devices were designed in silico. Drug and PLA were placed into the extruder to produce a 5% blend at 1.75-mm diameter. Material characterization included differential scanning calorimetry, thermogravimetric analysis plus inverse GC-surface energy analyzer. Results: Implantable constructs from the PLA feedstock were acquired. The extrusion processes had a detrimental effect on the active pharmaceutical ingredient-base blend. differential scanning calorimetry and thermogravimetric analysis analysis indicated drug–base interactions. Thermal history was found to influence inverse GC probe interaction. Conclusion: Drug-base incompatibilities must be considered during 3D printing.

Linking existing in vitro dermal absorption data to physicochemical properties: Contribution to the design of a weight-of-evidence approach for the safety evaluation of cosmetic ingredients with low dermal bioavailability

To characterize the risk of cosmetic ingredients when threshold toxicity is assumed, often the "margin of safety" (MoS) is calculated. This uncertainty factor is based on the systemic no observable (adverse) effect level (NO(A)EL) which can be derived from in vivo repeated dose toxicity studies. As in vivo studies for the purpose of the cosmetic legislation are no longer allowed in Europe and a validated in vitro alternative is not yet available, it is no longer possible to derive a NO(A)EL value for a new cosmetic ingredient. Alternatively, cosmetic ingredients with a low dermal bioavailability might not need repeated dose data, as internal exposure will be minimal and systemic toxicity might not be an issue. This study shows the possibility of identifying compounds suspected to have a low dermal bioavailability based on their physicochemical properties (molecular weight, melting point, topological polar surface area and log P) and their in vitro dermal absorption data. Although performed on a limited number of compounds, the study suggests a strategic opportunity to support the safety assessor's reasoning to omit a MoS calculation and to focus more on local toxicity and mutagenicity/genotoxicity for ingredients for which limited systemic exposure is to be expected.

Lowe D, Williams AJ. The development of models to predict melting and pyrolysis point data associated with several hundred thousand compounds mined from PATENTS

BACKGROUND

Melting point (MP) is an important property in regards to the solubility of chemical compounds. Its prediction from chemical structure remains a highly challenging task for quantitative structure-activity relationship studies. Success in this area of research critically depends on the availability of high quality MP data as well as accurate chemical structure representations in order to develop models. Currently, available datasets for MP predictions have been limited to around 50k molecules while lots more data are routinely generated following the synthesis of novel materials. Significant amounts of MP data are freely available within the patent literature and, if it were available in the appropriate form, could potentially be used to develop predictive models.

RESULTS

We have developed a pipeline for the automated extraction and annotation of chemical data from published PATENTS. Almost 300,000 data points have been collected and used to develop models to predict melting and pyrolysis (decomposition) points using tools available on the OCHEM modeling platform (http://ochem.eu). A number of technical challenges were simultaneously solved to develop models based on these data. These included the handing of sparse data matrices with >200,000,000,000 entries and parallel calculations using 32 × 6 cores per task using 13 descriptor sets totaling more than 700,000 descriptors. We showed that models developed using data collected from PATENTS had similar or better prediction accuracy compared to the highly curated data used in previous publications. The separation of data for chemicals that decomposed rather than melting, from compounds that did undergo a normal melting transition, was performed and models for both pyrolysis and MPs were developed. The accuracy of the consensus MP models for molecules from the drug-like region of chemical space was similar to their estimated experimental accuracy, 32 °C. Last but not least, important structural features related to the pyrolysis of chemicals were identified, and a model to predict whether a compound will decompose instead of melting was developed.

CONCLUSIONS

We have shown that automated tools for the analysis of chemical information have reached a mature stage allowing for the extraction and collection of high quality data to enable the development of structure-activity relationship models. The developed models and data are publicly available at http://ochem.eu/article/99826.

Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption

Oral absorption of compounds depends on many physiological, physiochemical and formulation factors. Two important properties that govern oral absorption are in vitro permeability and solubility, which are commonly used as indicators of human intestinal absorption. Despite this, the nature and exact characteristics of the relationship between these parameters are not well understood. In this study a large dataset of human intestinal absorption was collated along with in vitro permeability, aqueous solubility, melting point, and maximum dose for the same compounds. The dataset allowed a permeability threshold to be established objectively to predict high or low intestinal absorption. Using this permeability threshold, classification decision trees incorporating a solubility-related parameter such as experimental or predicted solubility, or the melting point based absorption potential (MPbAP), along with structural molecular descriptors were developed and validated to predict oral absorption class. The decision trees were able to determine the individual roles of permeability and solubility in oral absorption process. Poorly permeable compounds with high solubility show low intestinal absorption, whereas poorly water soluble compounds with high or low permeability may have high intestinal absorption provided that they have certain molecular characteristics such as a small polar surface or specific topology.