Small-molecule Active Pharmaceutical Ingredients Research Articles

High-throughput nanoscale crystallization of dihydropyridine active pharmaceutical ingredients.

Single-crystal X-ray diffraction analysis of small molecule active pharmaceutical ingredients is a key technique in the confirmation of molecular connectivity, including absolute stereochemistry, as well as the solid-state form. However, accessing single crystals suitable for X-ray diffraction analysis of an active pharmaceutical ingredient can be experimentally laborious, especially considering the potential for multiple solid-state forms (solvates, hydrates and polymorphs). In recent years, methods for the exploration of experimental crystallization space of small molecules have undergone a `step-change', resulting in new high-throughput techniques becoming available. Here, the application of high-throughput encapsulated nanodroplet crystallization to a series of six dihydropyridines, calcium channel blockers used in the treatment of hypertension related diseases, is described. This approach allowed 288 individual crystallization experiments to be performed in parallel on each molecule, resulting in rapid access to crystals and subsequent crystal structures for all six dihydropyridines, as well as revealing a new solvate polymorph of nifedipine (1,4-dioxane solvate) and the first known solvate of nimodipine (DMSO solvate). This work further demonstrates the power of modern high-throughput crystallization methods in the exploration of the solid-state landscape of active pharmaceutical ingredients to facilitate crystal form discovery and structural analysis by single-crystal X-ray diffraction.

Kinetic Optimization of the Batch Crystallization of an Active Pharmaceutical Ingredient in the Presence of a Low-Solubility, Precipitating Impurity

The presence of impurities above regulatory thresholds has been responsible for recent recalls of pharmaceutical drugs. Crystallization is one of the most used separation processes to control impurities in the final drug. A particular issue emerges when impurities are poorly soluble in the crystallization solvent and simultaneously precipitate with the product. This publication reports the development of a population balance model to investigate if the impurity crystallization kinetics can be selectively inhibited in a seeded batch crystallization system containing acetaminophen (ACM), a commonly used small-molecule active pharmaceutical ingredient (API), and curcumin (CUR), a simulated low-solubility/co-precipitating impurity. Raman spectroscopy was used in combination with a partial least squares (PLS) model for in situ monitoring of the crystallization process. The Raman data were integrated to calibrate a population balance model in gPROMS FormulatedProducts, to predict the evolution of the product’s purity throughout the process. Process optimization demonstrated that a high purity close to equilibrium is feasible within the first 2 h of crystallization, with ACM seed purity being the primary factor controlling this phenomenon. The optimal approach for kinetically rejecting impurities requires a low nucleation rate for the impurity, high product seed purities, and an adjustable crystallization time so the process can be stopped before equilibrium without allowing the impurity to nucleate. Overall, an improvement in product purity before equilibrium is attainable if there is enough difference in growth kinetics between the product and impurity, and if one can generate relatively pure seed crystals.

Computational intelligence modeling using Artificial Intelligence and optimization of processing of small-molecule API solubility in supercritical solvent

Preparation of small-molecule API (Active Pharmaceutical Ingredient) at submicron size would be of great benefit for pharmaceutical engineering, as the drug particles at submicron size possess higher solubility in water. Indeed, the drug bioavailability can be enhanced when the nanomedicine is prepared. In this study, the solubility of the drug desoxycorticosterone acetate (DA) is being examined to assess its viability of nanonization using supercritical operation. Two inputs are temperature and pressure which were considered for machine learning modeling in this study. The drug's solubility is the only output to be estimated by the optimized models. This dataset has 45 rows of data that were gathered at 5 different pressure and temperature levels. Support vector machine (SVM) is used as the core of the models built in this research. Epsilon-SVR and nu-SVR are models based on this concept, which together with two different polynomial and RBF kernels form the four models built in this research for estimation of DA drug solubility. The models are also optimized with the help of a new TLCO method. All four final models have an R2 score higher than 0.9, and among them, the Epsilon-SVR model with RBF kernel has the best performance with 0.967.

Development of advanced model for understanding the behavior of drug solubility in green solvents: Machine learning modeling for small-molecule API solubility prediction

Determination of small-molecule API (Active Pharmaceutical Ingredient) solubility in solvents is of great importance for drug development in pharmaceutical industry. This study uses machine learning algorithms to predict the solubility of phenytoin drug and density of the solvent at different pressure and temperature. In fact, the solubility of drug (y) and the density of supercritical CO2 (Sc-CO2) were investigated as functions of temperature (T) and pressure (P). Three regression models, namely Gaussian Process Regression (GPR), Gamma Regression (GR), and K-nearest neighbor (KNN) were employed to predict the output variables. To optimize the performance of these models, the Directional Bat Algorithm (dBA) was utilized for hyper-parameter tuning. The outputs demonstrated the accuracy of the developed models in predicting the Sc-CO2 density and solubility of phenytoin. Among the models, GPR exhibited the highest accuracy for both outputs, achieving an R2 value of 0.99 for the solvent density and 0.999 for the solubility. The root mean square error (RMSE) for Sc-CO2 density was approximately 18.37, with an average absolute relative deviation percentage (AARD%) of 4.07% and a maximum error of 37.42. For solubility, the RMSE was approximately 0.087, with an AARD% of 2.29% and a maximum error of 0.150.

Cocrystal Synthesis through Crystal Structure Prediction.

Crystal structure prediction (CSP) is an invaluable tool in the pharmaceutical industry because it allows to predict all the possible crystalline solid forms of small-molecule active pharmaceutical ingredients. We have used a CSP-based cocrystal prediction method to rank ten potential cocrystal coformers by the energy of the cocrystallization reaction with an antiviral drug candidate, MK-8876, and a triol process intermediate, 2-ethynylglyclerol. For MK-8876, the CSP-based cocrystal prediction was performed retrospectively and successfully predicted the maleic acid cocrystal as the most likely cocrystal to be observed. The triol is known to form two different cocrystals with 1,4-diazabicyclo[2.2.2]octane (DABCO), but a larger solid form landscape was desired. CSP-based cocrystal screening predicted the triol-DABCO cocrystal as rank one, while a triol-l-proline cocrystal was predicted as rank two. Computational finite-temperature corrections enabled determination of relative crystallization propensities of the triol-DABCO cocrystals with different stoichiometries and prediction of the triol-l-proline polymorphs in the free-energy landscape. The triol-l-proline cocrystal was obtained during subsequent targeted cocrystallization experiments and was found to exhibit an improved melting point and deliquescence behavior over the triol-free acid, which could be considered as an alternative solid form in the synthesis of islatravir.

A Robust HPLC Method for Easily Oxidizable Phosphine Ligand Analysis.

Phosphine ligands are widely used in the manufacture of small molecule active pharmaceutical ingredients, for they play a key role in transition-metal-catalyzed cross-coupling. However, chromatographic analysis of phosphine ligands can be challenging because of the easily oxidizable nature of this class of compounds. This manuscript describes an out-of-specification (OOS) investigation study of XPhos raw material analysis by high performance liquid chromatography (LC). It is concluded that on-column degradation/oxidation is the culprit behind this OOS result. In addition, a slightly modified yet much improved new LC method is developed by adding a trace amount of tris(2-carboxyethyl)phosphine (TCEP) into the aqueous mobile phase. TCEP is also a phosphine compound and is commonly used as a reducing reagent in molecular biology. The trace amount of TCEP serves as a surrogate reagent to passivate the LC column and eliminate the on-column degradation/oxidation. As a result, a much more robust performance is achieved with greatly improved method precision and sensitivity. This is a general approach and can be applied to the LC analysis of many other phosphine ligands in the same manner.

Quantitative nuclear magnetic resonanceof chloride by an accurate internal standard approach.

Chloride is the most common counterion used to improve aqueous solubility and enhance stability of small molecule active pharmaceutical ingredients. While several analytical techniques, such as titration, HPLC with charged aerosol detection, and ion chromatography, are currently utilized to assay the level of chloride, they have notable limitations, and these instruments may not be readily available. Here, we present a generally applicable 35 Cl solution NMR method to assay the level of chloride in pharmaceutical compounds. The method uses KClO4 as an internal standard for improved accuracy in comparison with external standard methods, and it was found to be robust, linear over three orders of magnitude, precise (<3% RSD), and accurate (<0.5% absolute error).

Simultaneous Spray Drying for Combination Dry Powder Inhaler Formulations.

Spray drying is a particle engineering technique used to manufacture respirable pharmaceutical powders that are suitable for delivery to the deep lung. It is amenable to processing both small molecules and biologic actives, including proteins. In this work, a simultaneous spray-drying process, termed simul-spray, is described; the process involves two different active pharmaceutical ingredient (API) solutions that are simultaneously atomized through separate nozzles into a single-spray dryer. Collected by a single cyclone, simul-spray produces a uniform mixture of two different active particles in a single-unit operation. While combination therapies for dry powder inhalers containing milled small molecule API are commercially approved, limited options exist for preparing combination treatments that contain both small molecule APIs and biotherapeutic molecules. Simul-spray drying is also ideal for actives which cannot withstand a milling-based particle engineering process, or which require a high dose that is incompatible with a carrier-based formulation. Three combination case studies are demonstrated here, in which bevacizumab is paired with erlotinib, cisplatin, or paclitaxel in a dry powder inhaler formulation. These model systems were chosen for their potential relevance to the local treatment of lung cancer. The resulting formulations preserved the biologic activity of the antibody, achieved target drug concentration, and had aerosol properties suitable for pulmonary delivery.

Japanese firms invest in APIs

Two Japanese chemical companies are increasing their presence in the active pharmaceutical ingredient (API) business. Sumitomo Chemical says it will build a third plant in Japan—this one in Oita City—for small-molecule APIs and intermediates. The firm says the project will enhance its leading position in Japan. Meanwhile, AGC says it will spend $100 million to expand its small-molecule API plant in Malgrat de Mar, Spain. AGC acquired the facility in 2019.

Open source anaerobic and temperature-controlled in vitro model enabling real-time release studies with live bacteria

In vitro release and dissolution models are widely used in the development phases of oral drug delivery systems to measure how an active pharmaceutical ingredient (API) is released from a dosage form. However, additional requirements for these models arise when evaluating probiotic dosage forms since they are often sensitive to temperature and oxygen levels. As a solution to this, we propose a custom-designed anaerobic in vitro release setup, made mainly by 3D printing and laser cutting, to function together with state-of-the-art pharmaceutical dissolution equipment – in this case, a microDISS Profiler™. The in vitro release model makes it possible to study the release rate of oxygen-sensitive probiotics in simulated intestinal conditions, while ensuring their survival due to the anaerobic conditions. This has not been possible so far since the available in vitro dissolution models have not been compatible with anaerobic conditions. With two different case studies, the developed model combined with a microDISS Profiler™ has proven capable of measuring the release of a probiotic and a small-molecule API from microdevices for oral drug delivery. Further, the model facilitated the survival of anaerobic bacteria present in the release medium.

Amide Bonds Meet Flow Chemistry: A Journey into Methodologies and Sustainable Evolution.

Formation of amide bonds is of immanent importance in organic and synthetic medicinal chemistry. Its presence in “traditional” small‐molecule active pharmaceutical ingredients, in linear or cyclic oligo‐ and polypeptidic actives, including pseudopeptides, has led to the development of dedicated synthetic approaches for the formation of amide bonds starting from, if necessary, suitably protected amino acids. While the use of solid supported reagents is common in traditional peptide synthesis, similar approaches targeting amide bond formation in continuous‐flow mode took off more significantly, after a first publication in 2006, only a couple of years ago. Most efforts rely upon the transition of traditional approaches in flow mode, or the combination of solid‐phase peptide synthesis principles with flow chemistry, and advantages are mainly seen in improving space‐time yields. This Review summarizes and compares the various approaches in terms of basic amide formation, peptide synthesis, and pseudopeptide generation, describing the technological approaches and the advantages that were generated by the specific flow approaches. A final discussion highlights potential future needs and perspectives in terms of greener and more sustainable syntheses.

Green and sustainable metrics: Charting the course for green-by-design small molecule API synthesis

Sustainable small molecule Active Pharmaceutical Ingredient (API) manufacturing starts at the onset of route development by employing a Green-by-Design strategy. Reliable metrics are imperative for setting targets and measuring process improvements throughout the development cycle. This article reviews some of the many tools and methods established to analyze and assess the greenness and sustainability of a process, each of which highlights different aspects of process efficiency, waste formation or overall environmental impact reduction. Most calculations, such as process mass intensity (PMI), are mass-based and do not consider the types of raw materials used. In contrast, a full life cycle assessment (LCA) offers detailed information about the “cradle to grave” environmental impact of a manufacturing route and its specific resources, but the high data requirements and long timelines are not conducive for multiple processes or repeated assessments during process optimization. To address these challenges, we introduce a Streamlined PMI-LCA Tool, developed in collaboration with the ACS Green Chemistry Institute Pharmaceutical Roundtable (ACS GCIPR), that combines PMI with a “cradle to gate” approach to include the environmental footprint of the synthesis’ raw materials. The frequent re-evaluation of a process continuously highlights areas for improvement and guides the prioritization of process development activities to effectively and rapidly achieve a Green-by-Design commercial synthetic route. The utility of this approach to Green-by-Design is demonstrated with the reduction of PMI for MK-7264 from 366 to 88 over the course of process development.

Manufacturing mass intensity: 15 ​Years of Process Mass Intensity and development of the metric into plant cleaning and beyond

The American Chemical Society Green Chemistry Institute (ACS GCI) Pharmaceutical Roundtable is committed to continue to expand and identify elements of small-molecule active pharmaceutical ingredient (API) manufacturing that should be quantified to drive towards more sustainable practices. Process mass intensity (PMI) has been used for over 15 years to evaluate and benchmark progress towards more sustainable manufacturing and quantifies process input mass (e.g. solvent, water, reagents) per mass of output produced. This manuscript introduces Manufacturing Mass Intensity (MMI), a metric that builds upon and expands the scope to account for other raw materials required for API manufacturing. Examples are included to illustrate how quantification of these additional resource requirements will drive more sustainable practices.

PDE concept for controlling cleaning agent residues in pharmaceuticals– A critical analysis

Cleaning agents (CAs) are used in multipurpose facilities to control carryover contamination of active pharmaceutical ingredients (APIs) to scientifically justified limits. While this is often done with the PDE methodology used for API impurities, it is unclear if it is justifiable and necessary for cleaning agents, which generally represent a comparatively lower health risk.Comparing calculated oral PDE values for CA ingredients (CAIs) from four companies with PDEs of a selected number of small-molecule APIs showed that the toxicity of CAIs is several orders of magnitude lower. Furthermore, a critical review of the toxicity and everyday exposure to the general population of the main CAIs functional groups showed that the expected health risks are generally negligible. This is particularly true if the associated mode of actions cause local toxicity that is usually irrelevant at the concentration of potential residue carryover.This work points towards alternative approaches to the PDE concept to control CAIs’ contamination and provides some guidance on grouping and identifying compounds with lower health risks based on exposure and mode of action reasoning. In addition, this work supports the concept that limit values should only be set for CAIs of toxicological concern.

Shortening Synthetic Routes to Small Molecule Active Pharmaceutical Ingredients Employing Biocatalytic Methods.

Biocatalysis, using enzymes for organic synthesis, has emerged as powerful tool for the synthesis of active pharmaceutical ingredients (APIs). The first industrial biocatalytic processes launched in the first half of the last century exploited whole-cell microorganisms where the specific enzyme at work was not known. In the meantime, novel molecular biology methods, such as efficient gene sequencing and synthesis, triggered breakthroughs in directed evolution for the rapid development of process-stable enzymes with broad substrate scope and good selectivities tailored for specific substrates. To date, enzymes are employed to enable shorter, more efficient, and more sustainable alternative routes toward (established) small molecule APIs, and are additionally used to perform standard reactions in API synthesis more efficiently. Herein, large-scale synthetic routes containing biocatalytic key steps toward >130 APIs of approved drugs and drug candidates are compared with the corresponding chemical protocols (if available) regarding the steps, reaction conditions, and scale. The review is structured according to the functional group formed in the reaction.

Quantitation and speciation of residual protein within active pharmaceutical ingredients using image analysis with SDS-PAGE

Recent advances in biocatalysis and directed enzyme evolution has led to a variety of enzymatically-driven, elegant processes for active pharmaceutical ingredient (API) production. For biocatalytic processes, quantitation of any residual protein within a given API is of great importance to ensure process robustness and quality, pure pharmaceutical products. Typical analytical methods for analyzing residual enzymes within an API, such as enzyme-linked immunosorbent assays (ELISA), colorimetric assays, and liquid chromatographic techniques, are limited for determining only the concentration of known proteins and require harsh solvents with high API levels for analysis. For the first time, total residual protein content in a small molecule API was quantitated using image analysis applied to SDS-PAGE. Herein, a proposed methodology for residual protein detection, quantitation, and size-based speciation is presented, in which an orthogonal technique is offered to traditional analysis methods, such as ELISA. Results indicate that our application of the analytical methodology is able to reliably quantitate both protein standards and the total residual protein present within a final API, with good agreement as compared to traditional ELISA results. Further, speciation of the residual protein within the API provides key information concerning the individual residual proteins present, including their molecular weight, which can lead to improved process development efforts for residual protein rejection and control. This analytical methodology thus offers an alternative tool for easily identifying, quantitating, and speciating residual protein content in the presence of small molecule APIs, with potential for wide applicability across industry for biocatalytic or directed enzyme evolution efforts within process development.

Curia to expand Rensselaer facility

Curia plans to spend $35 million to expand the capacity of its facility in Rensselaer, New York. The contract development and manufacturing organization, known until recently as AMRI, aims to more than double the site’s batch production capability for small-molecule active pharmaceutical ingredients (APIs), allowing it to meet growing demand for highly potent APIs. The expansion is expected to be completed in 18 months. Curia has several facilities in the US, as well as plants in France, Spain, Italy, and India.

Quantitation of Conjugation-related Residual Solvents in Antibody Drug Conjugates using Headspace Gas Chromatography

Background: Antibody Drug Conjugates (ADCs) are complex hybrid molecules comprised of a monoclonal antibody (mAb) connected to a small molecule drug through a linker. The key step in the production of ADCs is bringing together the protein in an aqueous buffer with a hydrophobic small molecule in order to achieve conjugation of the molecules. This step involves dissolving the small molecule portion of the compound in an aqueous miscible organic solvent. These solvents and unconjugated small molecules are ideally cleared by downstream processing in order to achieve the desired product quality. As part of the control system to ensure product quality, the determination of residual solvents in pharmaceuticals is of significant importance in order to protect patient safety and ensure an efficacious drug. Objective: Headspace gas chromatography (HS-GC) is the most widely used tool for quantification of residual solvents for small molecule active pharmaceutical ingredients (APIs) but is not widely used for the analysis of protein-containing samples. In this study, the detection of residual solvents in headspace injections was explored using various conditions in order to detect commonly used conjugation solvents including N,N-dimethylacetamide (DMA), N,N-dimethylformamide (DMF), dimethyl sulfoxide (DMSO), Ethylene Glycol (EG), and Propylene Glycol (PG) in an ADC drug product sample. Methods: Various organic solvents were explored to enhance the response observed with complex protein and residual solvent matrixes. As EG and PG do not partition into the headspace efficiently in the ADC drug product samples that contain large amounts of water, ionic liquids and other ionic compounds were screened with the ADC samples to see if they could improve the partitioning of the key solvents EG and PG. Results: Following headspace and chromatographic optimization, we have developed an approach for the detection and quantification of several conjugation reaction solvents in ADC samples. Conclusion: This new approach is an HS-GC method that simplifies Gas Chromatography (GC) analysis and sample preparation and can be readily implemented in quality control testing for bioconjugated products.

Novasep turns the corner

When Thermo Fisher Scientific purchased a viral vector business in Belgium earlier this year, all eyes were on the drug services giant as it added a European arm to the US viral vector operation it acquired for $1.7 billion in 2019. But the real action was arguably taking place at the midsize French firm that sold the business for $875 million. That company, Novasep, emerged from the sale with a clean balance sheet after spending nearly a decade working down debt accrued through mergers and acquisitions—a burden that nearly put it out of business. The deal also completed the process of remaking Novasep. It is now a contract development and manufacturing organization (CDMO) emphasizing small-molecule active pharmaceutical ingredient (API) production and tightly focused on customer molecules that are in late-stage clinical trials or on the market. Novasep managers credit that focus with delivering several months of phenomenal sales growth, resulting

Stabilization of Metastable Indomethacin α in Cellulose Nanocrystal Aerogel Scaffolds.

Indomethacin (IM) is a small molecule active pharmaceutical ingredient (API) that exhibits polymorphism with the γ-form being the most thermodynamically stable form of the drug. The α-form is metastable, but it exhibits higher solubility, making it a more attractive form for drug delivery. As with other metastable polymorphs, α-IM undergoes interconversion to the stable form when subjected to certain stimuli, such as solvent, heat, pH, or exposure to seed crystals of the stable form. In this study, IM was crystallized into cellulose nanocrystal aerogel scaffolds as a mixture of the two polymorphic forms, α-IM and γ-IM. Differential scanning calorimetry (DSC) and Raman spectroscopy were used to quantitatively determine the amount of each form. Our investigation found that the metastable α-IM could be stabilized within the aerogel without phase transformation, even in the presence of external stimuli, including heat and γ-IM seed crystals. Because interconversion is often a concern during production of metastable forms of APIs, this approach has important implications in being able to produce and stabilize metastable drug forms. While IM was used as a model drug in this study, this approach could be expanded to additional drugs and provide access to other metastable API forms.