Product Critical Quality Attributes Research Articles

Topical Semisolid Drug Product Critical Quality Attributes with Relevance to Cutaneous Bioavailability and Pharmacokinetics: Part I—Bioequivalence of Acyclovir Topical Creams

PurposeTo develop a toolkit of test methods for characterizing potentially critical quality attributes (CQAs) of topical semisolid products and to evaluate how CQAs influence the rate and extent of active ingredient bioavailability (BA) by monitoring cutaneous pharmacokinetics (PK) using an In Vitro Permeation Test (IVPT).MethodsProduct attributes representing the physicochemical and structural (Q3) arrangement of matter, such as attributes of particles and globules, were assessed for a set of test acyclovir creams (Aciclostad® and Acyclovir 1A Pharma) and compared to a set of reference acyclovir creams (Zovirax® US, Zovirax® UK and Zovirax® Australia). IVPT studies were performed with all these creams using heat-separated human epidermis, evaluated with both, static Franz-type diffusion cells and a flow through diffusion cell system.ResultsA toolkit developed to characterize quality and performance attributes of these acyclovir topical cream products identified certain differences in the Q3 attributes and the cutaneous PK of acyclovir between the test and reference sets of products. The cutaneous BA of acyclovir from the set of reference creams was substantially higher than from the set of test creams.ConclusionsThis research elucidates how differences in the composition or manufacturing of product formulations can alter Q3 attributes that modulate myriad aspects of topical product performance. The results demonstrate the importance of understanding the Q3 attributes of topical semisolid drug products, and of developing appropriate product characterization tests. The toolkit developed here can be utilized to guide topical product development, and to mitigate the risk of differences in product performance, thereby supporting a demonstration of bioequivalence (BE) for prospective topical generic products and reducing the reliance on comparative clinical endpoint BE studies.

An innovative hybrid modeling approach for simultaneous prediction of cell culture process dynamics and product quality.

The use of hybrid models is extensively described in the literature to predict the process evolution in cell cultures. These models combine mechanistic and machine learning methods, allowing the prediction of complex process behavior, in the presence of many process variables, without the need to collect a large amount of data. Hybrid models cannot be directly used to predict final product critical quality attributes, or CQAs, because they are usually measured only at the end of the process, and more mechanistic knowledge is needed for many classes of CQAs. The historical models can instead predict the CQAs better; however, they cannot directly relate manipulated process parameters to final CQAs, as they require knowledge of the process evolution. In this work, we propose an innovative modeling approach based on combining a hybrid propagation model with a historical data-driven model, that is, the combined hybrid model, for simultaneous prediction of full process dynamics and CQAs. The performance of the combined hybrid model was evaluated on an industrial dataset and compared to classical black-box models, which directly relate manipulated process parameters to CQAs. The proposed combined hybrid model outperforms the black-box model by 33% on average in predicting the CQAs while requiring only around half of the data for model training to match performance. Thus, in terms of model accuracy and experimental costs, the combined hybrid model in this study provides a promising platform for process optimization applications.

Developing a pharmaceutical fluid bed granulation & drying process via design of experiments based on a multivariate model

This manuscript presents a lean industrial workflow to establish an operating design space for a commercial scale fluid bed granulation and drying process. The workflow involves confirming the operating design space by demonstrating that the drug product critical quality attributes are met at the most extreme processing conditions within the granulation design space. This eliminates the need to execute a large experimental design, since any processing condition bound by the adequately demonstrated extreme conditions should also be acceptable, assuming linearity and continuity. A PLS (partial least squares) model was used to illustrate the multivariate relationship among the important process outputs and inputs (material properties and operating control variable settings). Since the moisture content of the fluidized bed influences granulation, the design space was evaluated based on the moisture accumulation and removal rates (output of the PLS models). The PLS model identified the specific experiments needed to confirm the operating design space. These specific experiments were executed, and the design space was confirmed experimentally. The PLS-model guided experimentation resulted in a lean experimental study while delivering a robust drug product manufacturing process.

Quality by Digital Design for Developing Platform RNA Vaccine and Therapeutic Manufacturing Processes.

Quality by digital design (QbDD) utilizes data-driven, mechanistic, or hybrid models to define and optimize a manufacturing design space. It improves upon the QbD approach used extensively in the pharmaceutical industry. The computational models developed in this approach identify and quantify the relationship between the product's critical quality attributes (CQAs) and the critical process parameters (CPPs) of unit operations within the manufacturing process. This chapter discusses the QbDD approach in developing and optimizing unit operations such as in vitro transcription, tangential flow filtration, affinity chromatography, and lipid nanoparticle (LNP) formulation in mRNA vaccine manufacturing. QbDD can be an efficient framework for developing a production process for a disease-agnostic product that requires extensive experimental and model-based process-product interaction characterization during the early process development phase.

Targeting fidelity of pharmaceutical systems models by optimization of precision on parameter estimates

Quantitative models have gained momentum to drive the development of pharmaceutical processes. The assessment of the prediction fidelity of these models is key to provide interpretability of process phenomena and to enable decision-making. Evaluating parametric uncertainty is paramount when the focus is on systems models, which combine different sub-models together, and, thus, parameters related to previous units may strongly impact the prediction of one final output. A framework is proposed to assess reliability in model predictions, where the precision of parameter estimates is explicitly optimized to target pre-set tolerance requirements on process key performance indicators and product critical quality attributes. A direct compression systems model for the manufacturing of oral solid dosage products is used as a case study. Results show that the proposed methodology is effective at guaranteeing the target model fidelity and at quantifying the maximum acceptable uncertainty in the estimates of model parameters.

The role of biospectroscopy and chemometrics as enabling technologies for upcycling of raw materials from the food industry

It is important to utilize the entire animal in meat and fish production to ensure sustainability. Rest raw materials, such as bones, heads, trimmings, and skin, contain essential nutrients that can be transformed into high-value products. Enzymatic protein hydrolysis (EPH) is a bioprocess that can upcycle these materials to create valuable proteins and fats. This paper focuses on the role of spectroscopy and chemometrics in characterizing the quality of the resulting protein product and understanding how raw material quality and processing affect it. The article presents recent developments in chemical characterisation and process modelling, with a focus on rest raw materials from poultry and salmon production. Even if some of the technology is relatively mature and implemented in many laboratories and industries, there are still open challenges and research questions. The main challenges are related to the transition of technology and insights from laboratory to industrial scale, and the link between peptide composition and critical product quality attributes.

Deep‐learning based in situ image monitoring crystal polymorph and size distribution: Modeling and validation

AbstractIn situ monitoring and closed‐loop control of the solution crystallization process are the modern trends for pharmaceutical development, in which the critical process parameters (CPPs) as well as the product critical quality attributes (CQAs) can be regulated and guaranteed during the manufacturing process. In this study, an in situ image monitoring methodology based on a state‐of‐the‐art deep‐learning model was developed to track the CQAs such as polymorph ratio, two‐dimensional crystal size, and crystal shape in a solvent‐mediated polymorphic transformation (SMPT) process. Coupled with the multidimensional process information, a 2D population balance model (PBM) was developed and validated using the results of the in situ image‐based CQAs analysis. The 2D‐PBM was solved using a high‐resolution finite volume method (HR‐FVM) which could provide a high dimensional particle‐size distribution. Through the validation between the process image analysis and the 2D‐PBM, the accuracy of image analysis was discussed, and the potential and challenges of in situ image analysis were proposed. This work aims to integrate the crystal polymorphism and two‐dimensional crystal size distribution (2D‐CSD) information in the SMPT process using intelligent microscopic image analysis and then to validate the results of neural network processing by solving the numerical solution of the multidimensional PBM.

Can Continuous Manufacturing of Topical Semisolids by Hot Melt Extrusion Soon Be a Reality?

For more than five decades, pharmaceutical manufacturers have been relying heavily on batch manufacturing that is a sequential, multistep, laborious, and time-consuming process. However, late advances in manufacturing technologies have prompted manufacturers to consider continuous manufacturing (CM) is a feasible manufacturing process that encompasses fewer steps and is less tedious and quick. Global regulatory agencies are taking a proactive role to facilitate pharmaceutical industries to adopt CM that assures product quality by employing robust manufacturing technologies encountering fewer interruptions, thereby substantially reducing product failures and recalls. However, adopting innovative CM is known to pose technical and regulatory challenges. Hot melt extrusion (HME) is one such state-of-the-art enabling technology that facilitates CM of diverse pharmaceutical dosage forms, including topical semisolids. Efforts have been made to continuously manufacture semisolids by HME integrating the principles of Quality by Design (QbD) and Quality Risk Management (QRM) and deploying Process Analytical Technologies (PAT) tools. Attempts have been made to systematically elucidate the effect of critical material attributes (CMA) and critical process parameters (CPP) on product critical quality attributes (CQA) and Quality Target Product Profiles (QTPP) deploying PAT tools. The article critically reviews the feasibility of one of the enabling technologies such as HME in CM of topical semisolids. The review highlights the benefits of the CM process and challenges ahead to implement the technology to topical semisolids. Once the CM of semisolids adopting melt extrusion integrated with PAT tools becomes a reality, the process can be extended to manufacture sterile semisolids that usually involve more critical processing steps.

Pharmaceutical hot melt extrusion process development using QbD and digital twins

Pharmaceutical product development guided by Quality by Design (QbD) is based on a complete understanding of the critical process parameters (CPPs) that are important for achieving the desired product critical quality attributes (CQAs). The effect of process settings, such as the screw speed, the throughput, the barrel temperature, and the screw configuration, is a well-known factor in the setup of pharmaceutical hot melt extrusion (HME) processes. A CPP that has not yet been extensively researched is the type of cross-section geometry of the screw elements. Typically, pharmaceutical extruders have double-flighted screw cross-sections, with some elements having a single- or triple-flighted element section. The exception is a NANO16 extruder from Leistritz, with all screw elements having a triple-flighted screw geometry. We investigated the process setup and scale-up to a double-flighted extruder experimentally and in silico via a digital twin. Two formulations were processed on a NANO16 extruder and virtually transferred to a ZSE18 double-flighted co-rotating twin-screw extruder. Detailed smoothed particle hydrodynamics simulations of all screw elements available from both extruders were performed, and their efficiency in conveying, pressure build-up, and power consumption were studied. Reduced-order 1D HME simulations, which were carried out to investigate the process space and scalability of both extruders, were experimentally validated.

Transcriptomic analysis reveals mode of action of butyric acid supplementation in an intensified CHO cell fed‐batch process

Process intensification is increasingly used in the mammalian biomanufacturing industry. The key driver of this trend is the need for more efficient and flexible production strategies to cope with the increased demand for biotherapeutics predicted in the next years. Therefore, such intensified production strategies should be designed, established, and characterized. We established a CHO cell process consisting of an intensified fed‐batch (iFB), which is inoculated by an N‐1 perfusion process that reaches high cell concentrations (100 × 106 c ml−1). We investigated the impact of butyric acid (BA) supplementation in this iFB process. Most prominently, higher cellular productivities of more than 33% were achieved, thus 3.5 g L−1 of immunoglobulin G (IgG) was produced in 6.5 days. Impacts on critical product quality attributes were small. To understand the biological mechanisms of BA in the iFB process, we performed a detailed transcriptomic analysis. Affected gene sets reflected concurrent inhibition of cell proliferation and impact on histone modification. These translate into subsequently enhanced mechanisms of protein biosynthesis: enriched regulation of transcription, messenger RNA processing and transport, ribosomal translation, and cellular trafficking of IgG intermediates. Furthermore, we identified mutual tackling points for optimization by gene engineering. The presented strategy can contribute to meet future requirements in the continuously demanding field of biotherapeutics production.

QbD-guided pharmaceutical development of Pembrolizumab biosimilar candidate PSG-024 propelled to industry meeting primary requirements of comparability to Keytruda®

Pharmaceutical development of biosimilars is primarily focused on meeting the regulatory requirements for analytical comparability of the product's critical quality attributes (CQAs), concerning safety and efficacy, to those of the originator drug of interest. To this end, the early adoption of a systematic science-based approach, as guided by quality-by-design (QbD) principles, is crucial due to the blind starting point where the same insights of an originator developer into the challenges of a given biopharmaceutical and its manufacturing process are lacking. In this study, we devised a pharmaceutical QbD-guided approach to undertake the biosimilar development of Pembrolizumab (Keytruda®), the ace of therapeutic monoclonal antibodies (mAbs) in terms of approved indications and market sales, and its manufacturing process development. Quality target product profile (QTPP) for Pembrolizumab biosimilar product was assembled using publicly available information on Keytruda®. Upon preliminary analyses of four different lots of Keytruda®, the product CQAs and their acceptable ranges of specification were determined via risk assessment based on the relevant pharmaceutical development quality guidelines, particularly those of the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH). The development and clone selection of Chinese Hamster Ovary (CHO) DG44 cell line was performed using DHFR expression vectors and Methotrexate (MTX) selective pressure. The CHO clone stably expressing relatively higher mAb titer (∼1200 mg/l) in small-scale shake-flask cultures, with the highest similarity of the CQAs charge variants contents (CVCs), N-glycan profile, and biological potency to those of Keytruda® reference standard was selected as the lead clone and the produced Pembrolizumab candidate was named PSG-024. The upstream process (USP) and downstream process (DSP) developments for production were started with the process evaluation screening experiments for the identification of critical process parameters (CPPs) founded upon the prior knowledge on different process stages, input process parameters (iPPs), output process parameters (oPPs), and their impacts on product CQAs. Thereby, screening experiments of USP fed-batch cell culture in 5-liter bioreactor resulted in improvement of PSG-024 expression titer to 2060 ± 70 mg/l and selection of the iPPs feed amount (A), glucose setpoint (B), culture temperature (C), and agitation rate (D) for the optimization design of experiments (DoEs) mainly focused on the CQA acidic CVC and the oPPs mAb expression yield. The USP optimization DoEs using response surface methodology (RSM) yielded valid prediction models and optimal conditions of A = 35%, B = 4.5 g/l, C = 37 °C, and D = 160–220 rpm, which resulted in the final PSG-024 expression titer of 3170 ± 40 mg/l without an excessive rise in acidic CVC. The DSP screening experiments led to achieving the mAb recovery rates of 94% ± 3% and 71.5% ± 3.5% for affinity (capture) and cation-exchange (polishing) chromatography stages, respectively. The capture eluate buffer and viral inactivation conditions were optimized to prevent mAb eluate turbidity and protein aggregation. Moreover, the polishing stage optimization DoEs via one-factor-at-a-time method focused on wash and elution steps for control of the acidic CVC CQA and achieving >80% mAb recovery rate. By shifting to Step elution from the primary salt gradient method and considering an additional intermediate wash step, the maximum mAb recovery of 87% ± 1.5% was achievable while maintaining the CQA acidic CVC within the acceptable range. The consistency of final analytical comparability of PSG-024 demonstrated the effectiveness of the adopted pharmaceutical QbD approach for Pembrolizumab biosimilar development, paving the way for the technology transfer to the client to proceed further development.

Harnessing the potential of machine learning for advancing “Quality by Design” in biomanufacturing

ABSTRACT Ensuring consistent high yields and product quality are key challenges in biomanufacturing. Even minor deviations in critical process parameters (CPPs) such as media and feed compositions can significantly affect product critical quality attributes (CQAs). To identify CPPs and their interdependencies with product yield and CQAs, design of experiments, and multivariate statistical approaches are typically used in industry. Although these models can predict the effect of CPPs on product yield, there is room to improve CQA prediction performance by capturing the complex relationships in high-dimensional data. In this regard, machine learning (ML) approaches offer immense potential in handling non-linear datasets and thus are able to identify new CPPs that could effectively predict the CQAs. ML techniques can also be synergized with mechanistic models as a ‘hybrid ML’ or ‘white box ML’ to identify how CPPs affect the product yield and quality mechanistically, thus enabling rational design and control of the bioprocess. In this review, we describe the role of statistical modeling in Quality by Design (QbD) for biomanufacturing, and provide a generic outline on how relevant ML can be used to meaningfully analyze bioprocessing datasets. We then offer our perspectives on how relevant use of ML can accelerate the implementation of systematic QbD within the biopharma 4.0 paradigm.

QUALITY BY DESIGN BASED DEVELOPMENT OF ETRAVIRINE SELF MICRO EMULSIFYING DRUG DELIVERY SYSTEM

Objective: The main objective of the present research work was to develop systematically the Self Micro Emulsifying Drug Delivery system of BCS Class IV drug in a Quality by Design framework.
 Methods: The quality by design-based formulation development proceeds with defining the Quality Target Product Profile and Critical Quality Attributes of dosage form with appropriate justification for the same. The statistical Mixture design was used for the development of the formulation. The independent variables selected for the design were Oleic acid, Labrasol and PEG 6000, whereas droplet size (nm), emulsification time (sec), % drug loading and % drug release at 15 min were considered as the potential quality attributes of the Self Micro Emulsifying System. The eight different batches of Etravirine-Self Micro Emulsifying systems (ETV-SMEDDS) were prepared and checked for the Critical Quality Attributes. The simultaneous optimization of the formulation was done by the global desirability approach.
 Results: The characterization report obtained for all the different batches of formulation was analyzed statistically by fitting into regression models. The statistically significant models determined for droplet size (nm) (R2= 0.96 and p-0.1022), emulsification time (sec) (R2= 0.99 and p-0.0267), % drug loading (R2= 0.93 and p-0.1667) and % drug release at 15 min (R2= 0.96 and p-0.0911) and were statistically significant. The maximal global desirability value obtained was 0.9415 and the value indicates, the selected factors and responses have a good correlation and are significant enough for optimization and prediction of best formulation.
 Conclusion: The QbD approach utilized during the development of ETV-SMEEDS facilitated the identification of Critical Material Attributes and their significant impact on the Critical Quality Attributes of SMEDDS. The concept of building quality into product through the QbD application was utilized successfully in the formulation development.

Quality Control Testing, Characterization and Critical Quality Attributes of Adeno-Associated Virus Vectors Used for Human Gene Therapy.

For adeno-associated virus (AAV)-based human gene therapy, challenges for the translation of promising research results to successful clinical development include optimization of vector design and manufacturing processes to ensure that vectors prepared for administration to human subjects have attributes consistent with safe and durable expression. This article briefly reviews quality control methods for routine testing and supplemental characterization of AAV vectors for investigational product development. The relationship of vector and manufacturing process design with product critical quality attributes is discussed.

Development of a Curcumin-Loaded Polymeric Microparticulate Oral Drug Delivery System for Colon Targeting by Quality-by-Design Approach.

The purpose of this study was to apply the quality-by-design (QbD) approach for the development of colon-targeted curcumin-loaded polymeric microparticles (Col-CUR-MPs). The proportion of the enterosoluble polymer (Eudragit® FS) in the polymeric matrix, curcumin concentration, and the concentration of the polymer mixture (Eudragit® FS-polycaprolactone) were identified as potential risk factors for the quality of the final product following risk assessment. The influence of these variables on the critical quality attributes (CQAs) of Col-CUR-MPs was investigated. Therefore, a central composite face experimental design was used in order to determine the functional relationships between variables and product CQAs. The obtained regression model and contour plots were used to establish the design space. Finally, the model was validated by preparing two microparticulate formulations, one corresponding to the robust setpoint from within the design space and one outside the established design space, and calculating the percentage bias between the experimental and predicted values. The in vivo study, which was conducted on a fluorescein-loaded formulation that corresponded to the robust setpoint determined by QbD and that contained a mixture of polycaprolactone and Eudragit® FS (60:40, w/w), confirmed the colon-targeting qualities of this formulation.

Development of freeze-drying cycle via design space approach: a case study on vaccines

Freeze-drying is a dehydration process that provides improved stability of vaccine formulations for shipment and storage. During the primary drying steps of the process, product temperature has to be maintained below a critical value to avoid visual defects of the product, leading to an increase of the sublimation time and thus of the operational costs. In this work, we used the design space approach together with experimental analysis for the development of the primary drying step of a vaccine model formulation. First, the formulation was characterized by determining the glass transition and the collapse temperatures. Successively, the dynamic design space of primary drying was calculated via mathematical modelling, and a proven acceptable range (PAR) was defined around the selected operating values. Finally, the cycle and the PAR were validated by performing a freeze-drying cycle at pilot scale and by evaluating the values of the product critical quality attributes (e.g. moisture content, visual aspect, reconstitution time).

Online/at‐line measurement, analysis and control of product titer and critical product quality attributes (CQAs) during process development

Process analytical technology (PAT) has been defined by the Food and Drug Administration as a system for designing, analyzing, and controlling manufacturing through timely measurements to ensure final product quality. Based on quality-by-design (QbD) principles, real-time or near-real-time data monitoring is essential for timely control of critical quality attributes (CQAs) to keep the process in a state of control. To facilitate next-generation continuous bioprocessing, deployment of PAT tools for real-time monitoring is integral for process understanding and control. Real-time monitoring and control of CQAs are essential to keep the process within the design space and align with the guiding principles of QbD. The contents of this manuscript are pertinent to the online/at-line monitoring of upstream titer and downstream product quality with timely process control. We demonstrated that an ultra-performance liquid chromatography (UPLC) system interfaced with a UPLC-process sample manager (UPLC-PSM) can be utilized to measure titer and CQAs directly from bioreactors and downstream unit operations, respectively. We established online titer measurements from fed-batch and perfusion-based alternating tangential flow bioreactors as well as product quality assessments of downstream operations for real-time peak collection. This integrated, fully automated system for online data monitoring with feedback control is designed to achieve desired product quality.

Functionality improvement of Chlorzoxazone by crystallo-co-agglomeration using multivariate analysis approach

The aim of present work was to improve physicochemical properties of model drug Chlorzoxazone by crystallo-co-agglomeration (CCA) in the presence of different polymers and excipients. Identification of Quality Target Product Profile and Critical Quality Attributes were done using Risk assessment and Failure mode effect analysis. CCA was formulated by applying Box–Behnken design followed by principal component analysis (PCA). CCA was further studied for its topographical, micromeritic, mechanical, compressional, and dissolution properties. Prepared CCA showed improvement in flow and packability with rich drug content (90.84%). Heckel parameters indicated greater plastic deformation (K = 0.8132) and tensile strength compared to the pure drug (K = 19.256 kg/cm2). CCA showed negligible elastic recovery (0.87%) compared to the pure drug (5.708%). Dissolution of the drug was increased to 2.69-folds compared to the pure drug after 60 min. No degradation or polymorphic transformation of the drug was observed even after stability study (40 °C, 75% RH). The amount of directly compressible diluents could be minimized in tablet formulation, which was a considerable improvement in the properties of the drug for making directly compressible form. The study highlights an improvement of processing characteristics of Chlorzoxazone by CCA using an integrated approach of QbD and PCA.

An alternative downstream process based on aqueous two-phase extraction for the purification of monoclonal antibodies

An alternative downstream process for the purification of a monoclonal antibody (mAb) based on aqueous two-phase extraction as clarification, capture and primary purification step was developed. For further purification unit operations which are commonly used for mAb platform processes were utilized. A diafiltration approach was used to combine virus inactivation and removal of phase forming components as well as low molecular weight impurities in one step followed by cation and anion exchange chromatography. Starting from cell containing cultivation broth, an overall mAb yield of 74 % was achieved within an application study. The process was optimized regarding mAb yield and the clearance of process related impurities like deoxyribonucleic acid as well as host cell proteins, which were removed to approximately 60 and 6000 ppm respectively. Critical product quality attributes, regarding glycosylation patterns, were also examined and remained unimpaired after the aqueous two-phase extraction. The alternative downstream process presented in this study offers great potential to improve mAb manufacturing.

Recent Advances in Co-processed APIs and Proposals for Enabling Commercialization of These Transformative Technologies

Optimized physical properties (e.g., bulk, surface/interfacial, and mechanical properties) of active pharmaceutical ingredients (APIs) are key to the successful integration of drug substance and drug product manufacturing, robust drug product manufacturing operations, and ultimately to attaining consistent drug product critical quality attributes. However, an appreciable number of APIs have physical properties that cannot be managed via routes such as form selection, adjustments to the crystallization process parameters, or milling. Approaches to control physical properties in innovative ways offer the possibility of providing additional and unique opportunities to control API physical properties for both batch and continuous drug product manufacturing, ultimately resulting in simplified and more robust pharmaceutical manufacturing processes. Specifically, diverse opportunities to significantly enhance API physical properties are created if allowances are made for generating co-processed APIs by introducing nonactive components (e.g., excipients, additives, carriers) during drug substance manufacturing. The addition of a nonactive coformer during drug substance manufacturing is currently an accepted approach for cocrystals, and it would be beneficial if a similar allowance could be made for other nonactive components with the ability to modify the physical properties of the API. In many cases, co-processed APIs could enable continuous direct compression for small molecules, and longer term, this approach could be leveraged to simplify continuous end-to-end drug substance to drug product manufacturing processes for both small and large molecules. As with any novel technology, the regulatory expectations for co-processed APIs are not yet clearly defined, and this creates challenges for commercial implementation of these technologies by the pharmaceutical industry. The intent of this paper is to highlight the opportunities and growing interest in realizing the benefits of co-processed APIs, exemplified by a body of academic research and industrial examples. This work will highlight reasons why co-processed APIs would best be considered as drug substances from a regulatory perspective and emphasize the areas where regulatory strategies need to be established to allow for commercialization of innovative approaches in this area.