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.

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.

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.

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.

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.

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.

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.

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.

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.

Adult and pediatric physiologically-based biopharmaceutics modeling to explain lamotrigine immediate release absorption process.

Physiologically-based biopharmaceutics modeling (PBBM) has potential to accelerate the development of new drug and formulations. An important application of PBBM is for special populations such as pediatrics that have pharmacokinetics dependent on the maturation process. Lamotrigine (LTG) is a Biopharmaceutics Classification System (BCS) II drug and is widely prescribed. Therefore, the goal of this study was to assess the biopharmaceutics risk of the low-soluble drug LTG when the ontogeny on gastrointestinal tract (GIT) physiological parameters are considered. An oral physiologically-based pharmacokinetic model and a PBBM were developed and verified using GastroPlus™ software for both adults and children (2-12 years old, 12-52 kg). The biopharmaceutics properties and GIT physiological parameters were evaluated by sensitivity analysis. High doses were simulated assuming a worst case scenario, that is, the dose of 200 mg for adults and 5 mg/kg (up to the maximum of 200 mg) for 2-year-old children. Although several authors have suggested that ontogeny may have an effect on gastrointestinal fluid volume, our study found no evidence of interference between fluid and dose volumes with in vivo dissolution of LTG. The most impactful parameter was found to be the gastric transit time. Therefore, the hypothesis is developed to examine whether LTG exhibits characteristics of a BCS II classification in vitro while showing BCS I-like behavior in vivo. This hypothesis could act as a base for conducting novel studies on model-informed precision dosing, tailored to specific populations and clinical conditions. In addition, it could be instrumental in assessing the influence of various release profiles on in vivo performance for both adult and pediatric populations.

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.

Role of Physiologically Based Biopharmaceutics Modeling (PBBM) in Fed Bioequivalence Study Waivers: Regulatory Outlook, Case Studies and Future Perspectives.

Over the past few decades, physiologically based biopharmaceutics modeling (PBBM) has demonstrated its utility in both new drug and generic product development. Applications of PBBM for fed bioequivalence study waivers is an upcoming area. Recently Innovation & Quality (IQ) consortium demonstrated utility of PBBM to avoid repeat food effect studies for new drugs. In the similar lines, the current manuscript aims to discuss role of PBBM in generic fed bioequivalence study waivers. Generic industry practices related to PBBM model development to predict fed bioequivalence was portrayed with special emphasis on fed bio-predictive media. Media that can simulate fed bioequivalence study outcome were discussed from practical perspective. In-depth analysis, collating the data from 36 products was performed to understand predictability of PBBM for fed bioequivalence. Cases where PBBM was successful to predict fed bioequivalence was correlated with BCS class, formulation category and type of food effect. Further, two case studies were presented wherein fed bioequivalence study waiver obtained with PBBM approach. Lastly, future direction in terms of fed bioequivalence study waivers, regulatory perspectives and best practices for PBBM were portrayed. Overall, this article paves a way to utilize PBBM for generic fed bioequivalence study waivers.

Neural Network Models for Predicting Solubility and Metabolism Class of Drugs in the Biopharmaceutics Drug Disposition Classification System (BDDCS).

BACKGROUND AND OBJECTIVE: The biopharmaceutics drug disposition classification system (BDDCS) categorizes drugs into four classes on the basis of their solubility and metabolism. This framework allows for the study of the pharmacokinetics of transporters and enzymatic metabolization on biopharmaceuticals, as well as drug-drug interactions in the body. The objective of the present study was to develop computational models by neural network models and structural parameters and physicochemical properties to estimate the class of a drug in the BDDCS system. METHODS: In this study, deep learning methods were utilized to explore the potential of artificial and convolutional neural networks (ANNs and CNNs) in predicting the BDDCS class of 721 substances. The structural parameters and physicochemical properties [Abraham solvation parameters, octanol-water partition (log P) and over the pH range 1-7.5 (log D), number of rotatable bonds, hydrogen bond acceptor numbers, as well as hydrogen bond donor count] are calculated with various software. These compounds were then split into a training set consisting of 602 molecules and a test set of 119 compounds to validate the models. RESULTS: The results of this study showed that neural network models using applied parameters of the drug, i.e., log D and Abraham solvation parameters, are able to predict the class of solubility and metabolism in the BDDCS system with good accuracy. CONCLUSIONS: Neural network models are well equipped to deal with the relations between the structural parameters and physicochemical properties of drugs and BDDCS classes. In addition, log D is a more suitable parameter compared with log P in predicting BDDCS.

Shifting the Focus from Dissolution to Permeation: Introducing the Meso-fluidic Chip for Permeability Assessment (MCPA).

In response to the growing ethical and environmental concerns associated with animal testing, numerous in vitro tools of varying complexity and biorelevance have been developed and adopted in pharmaceutical research and development. In this work, we present one of these tools, i.e., the Meso-fluidic Chip for Permeability Assessment (MCPA), for the first time. The MCPA combines an artificial barrier (PermeaPad®) with an organ-on-chip device (MIVO®) and real-time automated concentration measurements, to yield a sustainable, yet effortless method for permeation testing. The system offers three major physiological aspects, i.e., a biomimetic membrane, an optimal membrane interfacial area-to-donor-volume-ratio (A/V) and a physiological flow on the acceptor/basolateral side, which makes the MPCA an ideal candidate for mechanistic studies and excellent in vivo bioavailability predictions. We validated the method with a handful of assorted drug compounds in unstirred and stirred donor conditions, before exploring its applicability as a tool for dissolution/permeation testing on a BCS class III/I drug (pyrazinamide) crystalline adducts and BCS class II/IV (hydrocortisone) amorphous solid dispersions. The results were highly reproducible and clearly displayed the method's potential for evaluating the performance of enabling formulations, and possibly even predicting in vivo performance. We believe that, upon further development, the MCPA will serve as a useful in vitro tool that could push sustainability into pharmaceutics by refining, reducing and replacing animal testing in early-stage drug development.