Conventional vs Mechanistic IVIVC: A Comparative Study in Establishing Dissolution Safe Space for Extended Release Formulations.

The use of in vitro-in vivo correlation (IVIVC) for extended release oral dosage forms is an important technique that can avoid potential clinical studies. IVIVC has been a topic of discussion over the past two decades since the inception of USFDA guidance. It has been routinely used for biowaivers, establishment of dissolution safe space and clinically relevant dissolution specifications, for supporting site transfers, scale-up and post approval changes. Although conventional or mathematical IVIVC is routinely used, other approach such as mechanistic IVIVC can be of attractive choice as it integrates all the physiological aspects. In the present study, we have performed comparative evaluation of mechanistic and conventional IVIVC for establishment of dissolution safe space using divalproex sodium and tofacitinib extended release formulations as case examples. Conventional IVIVC was established using Phoenix and mechanistic IVIVC was set up using Gastroplus physiologically based biopharmaceutics model (PBBM). Virtual dissolution profiles with varying release rates were constructed around target dissolution profile using Weibull function. After internal and external validation, the virtual dissolution profiles were integrated into mechanistic and conventional IVIVC and safe space was established by absolute error and T/R ratio's methods. The results suggest that mechanistic IVIVC yielded wider safe space as compared to conventional IVIVC. The results suggest that a mechanistic approach of establishing IVIVC may be a flexible approach as it integrates physiological aspects. These findings suggest that mechanistic IVIVC has wider potential as compared to conventional IVIVC to gain wider dissolution safe space and thus can avoid potential clinical studies.

Validation of a Caco-2 microfluidic Chip model for predicting intestinal absorption of BCS Class I-IV drugs.

Oral delivery is considered the most patient preferred route of drug administration, however, the drug must be sufficiently soluble and permeable to successfully formulate an oral formulation. There have been advancements in the development of more predictive solubility and dissolution tools, but the tools that has been developed for permeability assays have not been validated as extensively as the gold-standard Caco-2 Transwell assay. Here, we evaluated Caco-2 intestinal permeability assay in Transwells and a commercially available microfluidic Chip using 19 representative Biopharmaceutics Classification System (BCS) Class I-IV compounds. For each selected compound, we performed a comprehensive viability test, quantified its apparent permeability (Papp), and established an in vitro in vivo correlation (IVIVC) to the human fraction absorbed (fa) in both culture conditions. Permeability differences were observed across the models as demonstrated by antipyrine (Transwell Papp: 38.5 ± 6.1 × 10-8 cm/s vs Chip Papp: 32.9 ± 11.3 × 10-8 cm/s) and nadolol (Transwell Papp: 0.6 ± 0.1 × 10-7 cm/s vs Chip Papp: 3 ± 1.2 × 10-7 cm/s). The in vitro in vivo correlation (IVIVC; Papp vs. fa) of the Transwell model (r2 = 0.59-0.83) was similar to the Chip model (r2 = 0.41-0.79), highlighting similar levels of predictivity. Comparing to historical data, our Chip Papp data was more closely aligned to native tissues assessed in Ussing chambers. This is the first study to comprehensively validate a commercial Gut-on-a-Chip model as a predictive tool for assessing oral absorption to further reduce our reliance on animal models.

Physiologically Based Biopharmaceutics Modeling (PBBM): Best Practices for Drug Product Quality, Regulatory and Industry Perspectives: 2023 Workshop Summary Report.

Physiologically based biopharmaceutics modeling (PBBM) is used to elevate drug product quality by providing a more accurate and holistic understanding of how drugs interact with the human body. These models are based on the integration of physiological, pharmacological, and pharmaceutical data to simulate and predict drug behavior in vivo. Effective utilization of PBBM requires a consistent approach to model development, verification, validation, and application. Currently, only one country has a draft guidance document for PBBM, whereas other major regulatory authorities have had limited experience with the review of PBBM. To address this gap, industry submitted confidential PBBM case studies to be reviewed by the regulatory agencies; software companies committed to training. PBBM cases were independently and collaboratively discussed by regulators, and academic colleagues participated in some of the discussions. Successful bioequivalence "safe space" industry case examples are also presented. Overall, six regulatory agencies were involved in the case study exercises, including ANVISA, FDA, Health Canada, MHRA, PMDA, and EMA (experts from Belgium, Germany, Norway, Portugal, Spain, and Sweden), and we believe this is the first time such a collaboration has taken place. The outcomes were presented at this workshop, together with a participant survey on the utility and experience with PBBM submissions, to discuss the best scientific practices for developing, validating, and applying PBBMs. The PBBM case studies enabled industry to receive constructive feedback from global regulators and highlighted clear direction for future PBBM submissions for regulatory consideration.

Effect of Food Composition on the PK of Isoniazid Quantitatively Explained Using Physiologically Based Biopharmaceutics Modeling.

This work shows the utilization of a physiologically based biopharmaceutics model (PBBM) to mechanistically explain the impact of diverse food types on the pharmacokinetics (PK) of isoniazid (INH) and acetyl-isoniazid (Ac-INH). The model was established and validated using published PK profiles for INH along with a combination of measured and predicted values for the physico-chemical and biopharmaceutical propertied of INH and Ac-INH. A dedicated ontogeny model was developed for N-acetyltransferase 2 (NAT2) in human integrating Michaelis Menten parameters for this enzyme in the physiologically based pharmacokinetic (PBPK) model tissues and in the gut, to explain the pre-systemic and systemic metabolism of INH across different acetylator types. Additionally, a novel equation was proposed to calculate the luminal drug degradation related to the presence of reducing sugars, using individual sugar molar concentrations in the meal. By incorporating luminal degradation into the model, adjusting bile salt concentrations and gastric emptying according to food type and quantity, the PBBM was able to accurately predict the negative effect of carbohydrate-rich diets on the PK of INH.

Liquisolid Technique: A Novel Technique with Remarkable Applications in Pharmaceutics.

Recently, it has been observed that newly developed drugs are lipophilic and have low aqueous solubility issues, which results in a lower dissolution rate and bioavailability of the drugs. To overcome these issues, the liquisolid technique, an innovative and advanced approach, comes into play. This technique involves the conversion of the drug into liquid form by dissolving it in non-volatile solvent and then converting the liquid medication into dry, free-flowing, and compressible form by the addition of carrier and coating material. It offers advantages like low cost of production, easy method of preparation, and compactable with thermo labile and hygroscopic drugs. It has been widely applied for BCS II drugs to enhance dissolution profile. Improving bioavailability, providing sustained release, minimizing pH influence on drug dissolution, and improving drug photostability are some of the other promising applications of this technology. This review article presents an overview of the liquisolid technique and its applications in formulation development.

Mechanistic Modeling of In Vitro Biopharmaceutic Data for a Weak Acid Drug: A Pathway Towards Deriving Fundamental Parameters for Physiologically Based Biopharmaceutic Modeling.

Mechanistic modeling of in vitro experiments using metabolic enzyme systems enables the extrapolation of metabolic clearance for in vitro-in vivo predictions. This is particularly important for successful clearance predictions using physiologically based pharmacokinetic (PBPK) modeling. The concept of mechanistic modeling can also be extended to biopharmaceutics, where in vitro data is used to predict the in vivo pharmacokinetic profile of the drug. This approach further allows for the identification of parameters that are critical for oral drug absorption in vivo. However, the routine use of this analysis approach has been hindered by the lack of an integrated analysis workflow. The objective of this tutorial is to (1) review processes and parameters contributing to oral drug absorption in increasing levels of complexity, (2) outline a general physiologically based biopharmaceutic modeling workflow for weak acids, and (3) illustrate the outlined concepts via an ibuprofen (i.e., a weak, poorly soluble acid) case example in order to provide practical guidance on how to integrate biopharmaceutic and physiological data to better understand oral drug absorption. In the future, we plan to explore the usefulness of this tutorial/roadmap to inform the development of PBPK models for BCS 2 weak bases, by expanding the stepwise modeling approach to accommodate more intricate scenarios, including the presence of diprotic basic compounds and acidifying agents within the formulation.

23 Congreso Nacional Farmacéutico / [23rd National Pharmaceutical Congress]

Bajo el lema Transformando la sanidad con el farmacéutico, el 23 Congreso Nacional Farmacéutico ha reunido en Valencia a más de 2.000 farmacéuticos de todos los ámbitos de la profesión, desde la óptica y la ortopedia, a la dermofarmacia, la investigación, la industria, la distribución, la alimentación, los análisis clínicos, la salud pública, la farmacia hospitalaria y, por supuesto, la farmacia comunitaria. (AU)

Drug solubility in biorelevant media in the context of an inhalation-based biopharmaceutics classification system (iBCS).

An inhalation-based Biopharmaceutics Classification System for pulmonary drugs (iBCS) holds the perspective to allow for scientifically sound prediction of differences in the in vivo performance of orally inhaled drug products (OIDPs). A set of nine drug substances were selected, that are administered via both the oral and pulmonary routes. Their solubility was determined in media representative for the oral (Fasted State Simulated Intestinal Fluid (FaSSIF)) and pulmonary (Alveofact medium and Simulated Lung Fluid (SLF)) routes of administration to confirm the need for a novel approach for inhaled drugs. The complexity of these media was then stepwise reduced with the purpose of understanding the contribution of their components to the solubilizing capacity of the media. A second reason for varying the complexity was to identify a medium that would allow robust but accurate dissolution testing. Hence, Hank's balanced salt solution (HBSS) as a medium used in many in vitro biological tests, non-buffered saline solution, and water were included. For some drug substances (salbutamol sulfate, tobramycin, isoniazid, and tiotropium bromide), no significant differences were observed between the solubility in the media used. For other drugs, however, we observed either just small (rifampicin, budesonide, salmeterol) or unexpectedly large differences (beclomethasone dipropionate). Based on the minimum theoretical solubility required for their common pulmonary dose in 10 ml of lung lining fluid, drug solubility was classified as either high or low. Two high solubility and two low solubility compounds were then selected for refined solubility testing in pulmonary relevant media by varying their content of phospholipids, surfactant proteins and other proteins. The solubility of drug substances in simulated lung lining fluids was found to be dependent on the physicochemical properties of the drug substance and the composition of the media. While a pulmonary dissolution medium that would fit all drugs could not be established, our approach may provide guidance for finding the most suitable dissolution medium for a given drug substance and better designing in vitro tests for predicting the in vivo performance of inhalable drug products.

Nanocrystal technologies in biomedical science: From the bench to the clinic.

The pharmaceutical industry is grappling with a pressing crisis in drug development characterized by soaring R&D costs, setbacks in blockbuster drug development due to poor aqueous solubility, and patent-related limitations on newly approved molecules. To combat these challenges, diverse strategies have emerged to enhance the solubility and dissolution rates of Biopharmaceutics Classification System (BCS) II and IV drug molecules. Enter drug nanocrystals, a revolutionary nanotechnology-driven, carrier-free colloidal drug delivery system. This review provides a comprehensive insight into nanocrystal strategies, stabilizer selection criteria, preparation methods, advanced characterization techniques, the evolving nanocrystal technological landscape, current market options, and exciting clinical prospects for reshaping the future of pharmaceuticals.

Rising role of 3D-printing in delivery of therapeutics for infectious disease.

Modern drug delivery to tackle infectious disease has drawn close to personalizing medicine for specific patient populations. Challenges include antibiotic-resistant infections, healthcare associated infections, and customizing treatments for local patient populations. Recently, 3D-printing has become a facilitator for the development of personalized pharmaceutic drug delivery systems. With a variety of manufacturing techniques, 3D-printing offers advantages in drug delivery development for controlled, fine-tuned release and platforms for different routes of administration. This review summarizes 3D-printing techniques in pharmaceutics and drug delivery focusing on treating infectious diseases, and discusses the influence of 3D-printing design considerations on drug delivery platforms targeting these diseases. Additionally, applications of 3D-printing in infectious diseases are summarized, with the goal to provide insight into how future delivery innovations may benefit from 3D-printing to address the global challenges in infectious disease.

Using molecularly dissolved drug concentrations in PBBMs improves the prediction of oral absorption from supersaturating formulations.

Predicting the absorption of drugs from enabling formulations is still challenging due to the limited capabilities of standard physiologically based biopharmaceutics models (PBBMs) to capture complex absorption processes. Amongst others, it is often assumed that both, molecularly and apparently dissolved drug in the gastrointestinal lumen are prone to absorption. A recently introduced method for measuring concentrations of molecularly dissolved drug in a dynamic in vitro dissolution setup using microdialysis has opened new opportunities to test this hypothesis and refine mechanistic PBBM approaches. In the present study, we compared results of PBBMs that used either molecularly or apparently dissolved concentrations in the simulated gastrointestinal lumen as input parameters. The in vitro dissolution data from three supersaturating formulations of Posaconazole (PCZ) were used as model input. The modeling outcome was verified using PCZ concentration vs. time profiles measured in human intestinal aspirates and in the blood plasma. When using apparently dissolved drug concentrations (i.e., the sum of colloid-associated and molecularly dissolved drug) the simulated systemic plasma exposures were overpredicted, most pronouncedly with the ASD-based tablet. However, if the concentrations of molecularly dissolved drug were used as input values, the PBBM resulted in accurate prediction of systemic exposures for all three PCZ formulations. The present study impressively demonstrated the value of considering molecularly dissolved drug concentrations as input value for PBBMs of supersaturating drug formulations.

Coupling Drug Dissolution with BCS.

PURPOSE: The purpose of this study is to develop a Temporal Biopharmaceutic Classification System (T-BCS), linking Finite Dissolution Time (F.D.T.) and Mean Dissolution Time (M.D.T.) for Class I/III drugs and Mean Dissolution Time for saturation (M.D.T.s.) for Class II/IV drugs. METHODS: These parameters are estimated graphically or by fitting dissolution models to experimental data and coupled with the dose-to-solubility ratio (q) for each drug normalized in terms of the actual volume of dissolution medium (900 mL). RESULTS: Class I/III drugs consistently exhibited q values less than 1, aligning with expectations based on their solubility, while some Class II/IV drugs presented a deviation from anticipated q values, with observations of q < 1. This irregularity was rendered to the dissolution volume of 250 mL used for biopharmaceutical classification purposes instead of 900 mL applied as well as the dual classification of some sparingly soluble drugs. Biowaivers were also analyzed in terms of M.D.T., F.D.T. estimates and the regulatory dissolution time limits for rapidly and very-rapidly dissolved drugs. CONCLUSIONS: The T-BCS is useful for establishing correlations and assessing the magnitude of M.D.T., F.D.T., or M.D.T.s. for inter- and intra-class comparisons of different drugs and provide relationships between these parameters across all the models that were utilized.

The role of artificial intelligence in generating original scientific research.

Artificial intelligence (AI) is a revolutionary technology that is finding wide application across numerous sectors. Large language models (LLMs) are an emerging subset technology of AI and have been developed to communicate using human languages. At their core, LLMs are trained with vast amounts of information extracted from the internet, including text and images. Their ability to create human-like, expert text in almost any subject means they are increasingly being used as an aid to presentation, particularly in scientific writing. However, we wondered whether LLMs could go further, generating original scientific research and preparing the results for publication. We taskedGPT-4, an LLM, to write an original pharmaceutics manuscript, on a topic that is itself novel. It was able to conceive a research hypothesis, define an experimental protocol, produce photo-realistic images of 3D printed tablets, generate believable analytical data from a range of instruments and write a convincing publication-ready manuscript with evidence of critical interpretation. The model achieved all this is less than 1 h. Moreover, the generated data were multi-modal in nature, including thermal analyses, vibrational spectroscopy and dissolution testing, demonstrating multi-disciplinary expertise in the LLM. One area in which the model failed, however, was in referencing to the literature. Since the generated experimental results appeared believable though, we suggest that LLMs could certainly play a role in scientific research but with human input, interpretation and data validation. We discuss the potential benefits and current bottlenecks for realising this ambition here.

Evaluating Utilization of Tiny-TIM to Assess the Effect of Food on the Absorptions of Oral Drugs and Its Application on Biopharmaceutical Modeling.

Safety and efficacy are the most critical factors for the development of modern medications. For oral drugs, evaluating drug exposure under various conditions is one of the most important outcomes for clinical trials. These data will help to better understand the safety and efficacy of new drugs. Studies involving potential drug-drug interactions, proton pump inhibitors, and intake of food are often conducted to assess the above. Among the above, the influence of food on exposure to the drug is one of the key data sets for regulatory submission. Since food may have either a positive or negative effect on drug exposure, it is important to obtain an early assessment of the food effect. To better forecast and plan for clinical studies, substantial efforts have been made in the industry to develop modeling and in-vitro and in-vivo assays. Despite the efforts, predicting the effect of food on exposure without integrating the dynamic of the gastrointestinal tract in the assessment remains challenging. In this study, we evaluated the utilization of the dynamic Gastro-Intestinal Model (Tiny-TIM) for the food effect of over 20 drugs/formulations in development or on the market that covers all BCS classes. In general, the Tiny-TIM predicted food effects were in good agreement with the reported data in humans. This suggests that Tiny-TIM can successfully capture the impact of physicochemical properties on absorption under the influence of food.

Current Applications of Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) in Pharmaceutical Analysis: Review.

The present review encompasses various applications of multivariate curve resolution- alternating least squares (MCR-ALS) as a promising data handling, which is issued by analytical techniques in pharmaceutics. It involves different sections starting from a concise theory of MCR-ALS and four detailed applications in drugs analysis. Dissolution, stability, polymorphism, and quantification are the main four detailed applications. The data generated by analytical techniques associated with MCR-ALS deals accurately with different challenges compared to other chemometric tools. For each reviewed purpose, it was explained how MCR-ALS was applied and detailed information was given. Different approaches were introduced to overcome challenges that limit the use of MCR-ALS efficiently in pharmaceutical mixture were also discussed.

iBCS: 3. A Biopharmaceutics Classification System for Orally Inhaled Drug Products.

In this article, we specify for the first time a quantitative biopharmaceutics classification system for orally inhaled drugs. To date, orally inhaled drug product developers have lacked a biopharmaceutics classification system like the one developed to navigate the development of immediate release of oral medicines. Guideposts for respiratory drug discovery chemists and inhalation product formulators have been elusive and difficult to identify due to the complexity of pulmonary physiology, the intricacies of drug deposition and disposition in the lungs, and the influence of the inhalation delivery device used to deliver the drug as a respirable aerosol. The development of an inhalation biopharmaceutics classification system (iBCS) was an initiative supported by the Product Quality Research Institute (PQRI). The goal of the PQRI iBCS working group was to generate a qualitative biopharmaceutics classification system that can be utilized by inhalation scientists as a "rule of thumb" to identify desirable molecular properties and recognize and manage CMC product development risks based on physicochemical properties of the drug and the deposited lung dose. Herein, we define the iBCS classes quantitatively according to the dose number and permeability. The proposed iBCS was evaluated for its ability to categorize marketed inhaled drugs using data from the literature. The appropriateness of the classification of each drug was assessed based on published development, clinical and nonclinical data, and mechanistic physiologically based biopharmaceutics modeling. The inhaled drug product development challenges for each iBCS classification are discussed and illustrated for different classes of marketed inhaled drugs. Finally, it is recognized that discriminatory laboratory methods to characterize regional lung deposition, dissolution, and permeability will be key to fully realizing the benefits of an iBCS to streamline and derisk inhaled drug development.

Biowaiver Monograph for Immediate-Release Solid Oral Dosage Forms: Isavuconazonium Sulfate.

A Biopharmaceutics Classification System (BCS)-based biowaiver monograph is presented for isavuconazonium sulfate. A BCS-based biowaiver is a regulatory option to substitute appropriate in vitro data for in vivo bioequivalence studies. Isavuconazonium sulfate is the prodrug of isavuconazole, a broad-spectrum azole antifungal indicated for invasive fungal infections. While the prodrug can be classified as a BCS Class III drug with high solubility but low permeability, the parent drug can be classified as a BCS Class II drug with low solubility but high permeability. Interestingly, the in vivo behavior of both is additive and leads isavuconazonium sulfate to act like a BCS class I drug substance after oral administration. In this work, experimental solubility and dissolution data were evaluated and compared with available literature data to investigate whether it is feasible to approve immediate release solid oral dosage forms containing isavuconazonium sulfate according to official guidance from the FDA, EMA and/or ICH. The risks associated with waiving a prodrug according to the BCS-based biowaiver guidelines are reviewed and discussed, noting that current regulations are quite restrictive on this point. Further, results show high solubility but instability of isavuconazonium sulfate in aqueous media. Although experiments on the dissolution of the capsule contents confirmed 'very rapid' dissolution of the active pharmaceutical ingredient (API) isavuconazonium sulfate, its release from the commercial marketed capsule formulation Cresemba is limited by the choice of capsule shell material, providing an additional impediment to approval of generic versions via the BCS-Biowaiver approach.