Head-to-Head Comparison of Caco-2 Transwell and Gut-on-a-Chip Models for Assessing Oral Peptide Formulations.

Oral delivery of potent peptide drugs provides key formulation challenges in the pharmaceutical industry: stability, solubility, and permeability. Intestinal permeation enhancers (PEs) can overcome the low oral bioavailability by improving the drug permeability. Conventional in vitro and ex vivo models for assessing PEs fail to predict efficacy in vivo. Here, we compared Caco-2 cells cultured in the conventional static Transwell model to a commercially available continuous flow microfluidic Gut-on-a-Chip model. We determined baseline permeability of FITC-Dextan 3 kDa (FD3) in Transwell (5.3 ± 0.8 × 10-8 cm/s) vs Chip (3.2 ± 1.8 × 10-7 cm/s). We screened the concentration impact of two established PEs sodium caprate and sucrose monolaurate and indicated a requirement for higher enhancer concentration in the Chip model to elicit equivalent efficacy e.g., 10 mM sodium caprate in Transwells vs 25 mM in Chips. Fasted and fed state simulated intestinal fluids (FaSSIF/FeSSIF) were introduced into the Chip and increased basal FD3 permeability by 3-fold and 20-fold, respectively, compared to 4-fold and 4000-fold in Transwells. We assessed the utility of this model to peptides (Insulin and Octreotide) with PEs and observed much more modest permeability enhancement in the Chip model in line with observations in ex vivo and in vivo preclinical models. These data indicate that microfluidic Chip models are well suited to bridge the gap between conventional in vitro and in vivo models.

Parameterization of Physiologically Based Biopharmaceutics Models: Workshop Summary Report.

This Article shares the proceedings from the August 29th, 2023 (day 1) workshop "Physiologically Based Biopharmaceutics Modeling (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives". The focus of the day was on model parametrization; regulatory authorities from Canada, the USA, Sweden, Belgium, and Norway presented their views on PBBM case studies submitted by industry members of the IQ consortium. The presentations shared key questions raised by regulators during the mock exercise, regarding the PBBM input parameters and their justification. These presentations also shed light on the regulatory assessment processes, content, and format requirements for future PBBM regulatory submissions. In addition, the day 1 breakout presentations and discussions gave the opportunity to share best practices around key questions faced by scientists when parametrizing PBBMs. Key questions included measurement and integration of drug substance solubility for crystalline vs amorphous drugs; impact of excipients on apparent drug solubility/supersaturation; modeling of acid-base reactions at the surface of the dissolving drug; choice of dissolution methods according to the formulation and drug properties with a view to predict the in vivo performance; mechanistic modeling of in vitro product dissolution data to predict in vivo dissolution for various patient populations/species; best practices for characterization of drug precipitation from simple or complex formulations and integration of the data in PBBM; incorporation of drug permeability into PBBM for various routes of uptake and prediction of permeability along the GI tract.

PBBM Considerations for Base Models, Model Validation, and Application Steps: Workshop Summary Report.

The proceedings from the 30th August 2023 (Day 2) of the workshop "Physiologically Based Biopharmaceutics Models (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives" are provided herein. Day 2 covered PBBM case studies from six regulatory authorities which provided considerations for model verification, validation, and application based on the context of use (COU) of the model. PBBM case studies to define critical material attribute (CMA) specification settings, such as active pharmaceutical ingredient (API) particle size distributions (PSDs) were shared. PBBM case studies to define critical quality attributes (CQAs) such as the dissolution specification setting or to define the bioequivalence safe space were also discussed. Examples of PBBM using the credibility assessment framework, COU and model risk assessment, as well as scientific learnings from PBBM case studies are provided. Breakout session discussions highlighted current trends and barriers to application of PBBMs including: (a) PBBM credibility assessment framework and level of validation, (b) use of disposition parameters in PBBM and points to consider when iv data are not available, (c) conducting virtual bioequivalence trials and dealing with variability, (d) model acceptance criteria, and (e) application of PBBMs for establishing safe space and failure edges.

IVIVC Revised.

PURPOSE: To revise the IVIVC considering the physiologically sound Finite Absorption Time (F.A.T.) and Finite Dissolution Time (F.D.T.) concepts. METHODS: The estimates τ and τd for F.A.T. and F.D.T., respectively are constrained by the inequality τd ≤ τ; their relative magnitude is dependent on drug's BCS classification. A modified Levy plot, which includes the time estimates for τ and τd was developed. IVIVC were also considered in the light of τ and τd estimates. The modified Levy plot of theophylline, a class I drug, coupled with the rapid (30 min) and very rapid (15 min) dissolution time limits showed that drug dissolution/absorption of Class I drugs takes place in less than an hour. We reanalyzed a carbamazepine (Tegretol) bioequivalence study using PBFTPK models to reveal its complex absorption kinetics with two or three stages. RESULTS: The modified Levy plot unveiled the short time span (~ 2 h) of the in vitro dissolution data in comparison with the duration of in vivo dissolution/absorption processes (~ 17 h). Similar results were observed with the modified IVIVC plots. Analysis of another set of carbamazepine data, using PBFTPK models, confirmed a three stages absorption process. Analysis of steady-state (Tegretol) data from a paediatric study using PBFTPK models, revealed a single input stage of duration 3.3 h. The corresponding modified Levy and IVIVC plots were found to be nonlinear. CONCLUSIONS: The consideration of Levy plots and IVIVC in the light of the F.A.T. and F.D.T. concepts allows a better physiological insight of the in vitro and in vivo drug dissolution/absorption processes.

Explaining in-vitro to in-vivo efficacy correlations in oncology pre-clinical development via a semi-mechanistic mathematical model.

In-vitro to in-vivo correlations (IVIVC), relating in-vitro parameters like IC50 to in-vivo drug exposure in plasma and tumour growth, are widely used in oncology for experimental design and dose decisions. However, they lack a deeper understanding of the underlying mechanisms. Our paper therefore focuses on linking empirical IVIVC relations for small-molecule kinase inhibitors with a semi-mechanistic tumour-growth model. We develop an approach incorporating parameters like the compound's peak-trough ratio (PTR), Hill coefficient of in-vitro dose-response curves, and xenograft-specific properties. This leads to formulas for determining efficacious doses for tumor stasis under linear pharmacokinetics equivalent to traditional empirical IVIVC relations, but enabling more systematic analysis. Our findings reveal that in-vivo xenograft-specific parameters, specifically the growth rate (g) and decay rate (d), along with the average exposure, are generally more significant determinants of tumor stasis and effective dose than the compound's peak-trough ratio. However, as the Hill coefficient increases, the dependency of tumor stasis on the PTR becomes more pronounced, indicating that the compound is more influenced by its maximum or trough values rather than the average exposure. Furthermore, we discuss the translation of our method to predict population dose ranges in clinical studies and propose a resistance mechanism that solely relies on specific in-vivo xenograft parameters instead of IC50 exposure coverage. In summary, our study aims to provide a more mechanistic understanding of IVIVC relations, emphasizing the importance of xenograft-specific parameters and PTR on tumor stasis.

Lipid-Gelucire based rectal delivery of ramipril prodrug exhibits significant lowering of intra-ocular pressure in normotensive rabbit: sustained structural relaxation release kinetics and IVIVC.

Carboxylesterase enzymes convert a prodrug ramipril into the biologically active metabolite ramiprilat. It is prescribed for controlling ocular hypertension after oral administration. High concentrations of carboxylesterase enzymes in rectal and colon tissue can transform ramipril significantly to ramiprilat. Sustained rectal delivery of ramipril has been developed for intra-ocular pressure lowering effect using a normotensive rabbit model. Rectal suppositories have been formulated using a matrix base of HPMC K100-PEG 400-PEG 6000, incorporating varying amounts of Gelucire by the fusion moulding method. The presence of Gelucire in the suppository exhibited sustained structural relaxation-based release kinetics of RM compared to its absence. Intravenous and oral administration of ramipril has decreased IOP in the treated rabbit up to 90 and 360 min, respectively. Treated rabbits with suppositories have revealed decreased IOP for an extended period compared to the above. Formulation containing GEL 3% reduced intra-ocular pressure to 540 min, with the highest area under the decreased IOP curve. Compared to oral, the pharmacodynamic bioavailability of ramipril has been improved significantly using a sustained-release rectal suppository. A rectal suppository for sustained delivery of ramipril could be used to lower IOP significantly.

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.

Insights into Intra Periodontal Pocket Pathogenesis, Treatment, In Vitro-In Vivo Models, Products and Patents, Challenges and Opportunity.

Periodontal disease is a multifactorial pathogenic condition involving microbial infection, inflammation, and various systemic complications. Here, a systematic and comprehensive review discussing key-points such as the pros and cons of conventional methods, new advancements, challenges, patents and products, and future prospects is presented. A systematic review process was adopted here by using the following keywords: periodontal diseases, pathogenesis, models, patents, challenges, recent developments, and 3-D printing scaffolds. Search engines used were "google scholar", "web of science", "scopus", and "pubmed", along with textbooks published over the last few decades. A thorough study of the published data rendered an accurate and deep understanding of periodontal diseases, the gap of research so far, and future opportunities. Formulation scientists and doctors need to be interconnected for a better understanding of the disease to prescribe a quality product. Moreover, prime challenges (such as a lack of a vital testing model, scarcity of clinical and preclinical data, products allowing for high drug access to deeper tissue regions for prolonged residence, lack of an international monitoring body, lack of 4D or time controlled scaffolds, and lack of successful AI based tools) exist that must be addressed for designing new quality products. Generally, several products have been commercialized to treat periodontal diseases with certain limitations. Various strategic approaches have been attempted to target certain delivery regions, maximize residence time, improve efficacy, and reduce toxicity. Conclusively, the current review summarizes valuable information for researchers and healthcare professional to treat a wide range of periodontal diseases.

A Symbolic Regression Model for the Prediction of Drug Binding to Human Liver Microsomes.

It is common practice in the early drug discovery process to conduct in vitro screening experiments using liver microsomes in order to obtain an initial assessment of test compound metabolic stability. Compounds which bind to liver microsomes are unavailable for interaction with the drug metabolizing enzymes. As such, assessment of the unbound fraction of compound available for biotransformation is an important factor for interpretation of in vitro experimental results and to improve prediction of the in vivo metabolic clearance. Various in silico methods have been proposed for the prediction of test compound binding to microsomes, from various simple lipophilicity-based models with moderate performance to sophisticated machine learning models which demonstrate superior performance at the cost of increased complexity and higher data requirements. In this work, we attempt to strike a middle ground by developing easily implementable equations with improved predictive performance. We employ a symbolic regression approach based on a medium-size in-house data set of fraction unbound in human liver microsomes measurements allowing the identification of novel equations with improved performance. We validate the model performance on an in-house held-out test set and an external validation set.

A Perspective on Model-Informed IVIVC for Development of Subcutaneous Injectables.

Subcutaneously administered drugs are growing in popularity for both large and small molecule drugs. However, development of these systems - particularly generics - is slowed due to a lack of formal guidance regarding preclinical testing and in vitro - in vivo correlations (IVIVC). Many of these methods, while appropriate for oral drugs, may not be optimized for the complex injection site physiologies, and release rate and absorption mechanisms of subcutaneous drugs. Current limitations for formulation design and IVIVC can be supported by implementing mechanistic, computational methods. These methods can help to inform drug development by identifying key drug and formulation attributes, and their effects on drug release rates. This perspective, therefore, addresses current guidelines in place for oral IVIVC development, how they may differ for subcutaneously administered compounds, and how modeling and simulation can be implemented to inform design of these products. As such, integration of modeling and simulation with current IVIVC systems can help in driving the development of subcutaneous injectables.

Mechanistic Static Model based Prediction of Transporter Substrate Drug-Drug Interactions Utilizing Atorvastatin and Rifampicin.

OBJECTIVE: An in vitro relative activity factor (RAF) technique combined with mechanistic static modeling was examined to predict drug-drug interaction (DDI) magnitude and analyze contributions of different clearance pathways in complex DDIs involving transporter substrates. Atorvastatin and rifampicin were used as a model substrate and inhibitor pair. METHODS: In vitro studies were conducted with transfected HEK293 cells, hepatocytes and human liver microsomes. Prediction success was defined as predictions being within twofold of observations. RESULTS: The RAF method successfully translated atorvastatin uptake from transfected cells to hepatocytes, demonstrating its ability to quantify transporter contributions to uptake. Successful translation of atorvastatin's in vivo intrinsic hepatic clearance (CLint,h,in vivo) from hepatocytes to liver was only achieved through consideration of albumin facilitated uptake or through application of empirical scaling factors to transporter-mediated clearances. Transporter protein expression differences between hepatocytes and liver did not affect CLint,h,in vivo predictions. By integrating cis and trans inhibition of OATP1B1/OATP1B3, atorvastatin-rifampicin (single dose) DDI magnitude could be accurately predicted (predictions within 0.77-1.0 fold of observations). Simulations indicated that concurrent inhibition of both OATP1B1 and OATP1B3 caused approximately 80% of atorvastatin exposure increases (AUCR) in the presence of rifampicin. Inhibiting biliary elimination, hepatic metabolism, OATP2B1, NTCP, and basolateral efflux are predicted to have minimal to no effect on AUCR. CONCLUSIONS: This study demonstrates the effective application of a RAF-based translation method combined with mechanistic static modeling for transporter substrate DDI predictions and subsequent mechanistic interpretation.

Microsponge-derived mini tablets loaded with immunosuppressive agents: Pharmacokinetic investigation in human volunteers, cell viability and IVIVC correlation.

Sirolimus, a potent immunosuppressant, has been demonstrated to have remarkable activity in inhibiting allograft rejection in transplantation. The objective of the study was to fabricate microsponge mini tablets with enhanced solubility and bioavailability. ß-Cyclodextrin and NEOCEL C91 were selected to prepare the microsponges (SLM-M) to improve the stability and solubility of sirolimus. The current study involved the quasi emulsion-solvent diffusion technique to design sirolimus-loaded microsponges that were further compressed into mini tablets 4 mm in diameter. Solid-state characterization, dissolution at different pH values, stability, and pharmacokinetic profiles with IVIVC data were analyzed in humans. Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), and X-ray diffraction (XRD) were used to characterize the formulations, and high-performance liquid chromatography (HPLC) was used to assess the drug stability of the compressed microsponge minitablets. The API changed from the crystalline state to an amorphous state, as shown by XRD and DSC. The compressed mini tablets showed a 4-fold enhancement in the drug dissolution profile. A toxicology investigation suggested that mini tablets were safe. In humans, the bioavailability of sirolimus compressed mini tablets from SLM-M was significantly improved. The results suggest that mini tablets prepared with ß-cyclodextrin and NEOCEL C91 by a quasi emulsion-solvent diffusion process might be an alternative way to improve the bioavailability of sirolimus. In addition, the manufacturing process is easily scalable for the commercialization of drugs to market.

Development of an In Vitro System To Emulate an In Vivo Subcutaneous Environment: Small Molecule Drug Assessment.

A reliable in vitro system can support and guide the development of subcutaneous (SC) drug products. Although several in vitro systems have been developed, they have some limitations, which may hinder them from getting more engaged in SC drug product development. This study sought to develop a novel in vitro system, namely, Emulator of SubCutaneous Absorption and Release (ESCAR), to better emulate the in vivo SC environment and predict the fate of drugs in SC delivery. ESCAR was designed using computer-aided design (CAD) software and fabricated using the three-dimensional (3D) printing technique. ESCAR has a design of two acceptor chambers representing the blood uptake pathway and the lymphatic uptake pathway, respectively, although only the blood uptake pathway was investigated for small molecules in this study. Via conducting a DoE factor screening study using acetaminophen solution, the relationship of the output (drug release from the "SC" chamber to the "blood circulation" chamber) and the input parameters could be modeled using a variety of methods, including polynomial equations, machine learning methods, and Monte Carlo simulation-based methods. The results suggested that the hyaluronic acid (HA) concentration was a critical parameter, whereas the influence of the injection volume and injection position was not substantial. An in vitro-in vivo correlation (IVIVC) study was developed using griseofulvin suspension to explore the feasibility of applying ESCAR in formulation development and bioequivalence studies. The developed LEVEL A IVIVC model demonstrated that the in vivo PK profile could be correlated with the in vitro release profile. Therefore, using this model, for new formulations, only in vitro studies need to be conducted in ESCAR, and in vivo studies might be waived. In conclusion, ESCAR had important implications for research and development and quality control of SC drug products. Future work would be focused on further optimizing ESCAR and expanding its applications via assessing more types of molecules and formulations.

Efficient Evaluation of In Vivo Performance in Human for Generic Formulation by Novel Dissolution-Absorption Prediction (DAP) Workflow.

PURPOSE: The pharmaceutical bioequivalence of generic medicines must be confirmed with corresponding original drugs. Although the in vitro dissolution tests are required, results of the mandatory in vitro study do not necessarily reflect the in vivo performance after oral administration. Then, we have tried to develop the novel "Dissolution-Absorption Prediction (DAP) workflow" to evaluate the in vivo performance of generic medicines. METHODS: The DAP workflow consists of an "In vitro two-cell connected dissolution (TCCD) system" mimicking the changes in the luminal pH associated with gastrointestinal transit of medicines, "Evaluation of pharmacokinetics of active pharmaceutical ingredient (API)" and "Prediction of plasma concentration-time profile". TCCD system-evaluated dissolution kinetics of APIs from generic formulations and pharmacokinetic parameters based on human data regarding the original drugs were used to calculate the plasma concentration-time profiles of APIs after the oral administration of generic medicines. RESULTS: The mandatory in vitro dissolution tests indicated that the dissolution properties of valsartan (BCS class II) and fexofenadine (BCS class III/IV) in generic formulations did not coincide with those in the corresponding original formulations. The TCCD system provided the very similar dissolution kinetics for the generic and original formulations for the two APIs. Plasma concentration-time profiles evaluated utilizing the dissolution profiles obtained by the TCCD system were in good agreement with the observed profiles for both the generic and original formulations for each API. CONCLUSIONS: The DAP workflow would be valuable for estimating the in vivo performance of generic formulation and deducing their bioequivalence with the original formulation.

Development and Use of an Ex-Vivo In-Vivo Correlation to Predict Antiepileptic Drug Clearance in Patients Undergoing Continuous Renal Replacement Therapy.

OBJECTIVES: Results from previous ex-vivo continuous renal replacement therapy (CRRT) models have successfully demonstrated similar extraction coefficients (EC) identified from in-vivo clinical trials. The objectives of this study are to develop an ex-vivo in-vivo correlation (EVIVC) model to predict drug clearance for commonly used antiepileptics and to evaluate similarity in drug extraction across different CRRT modalities to extrapolate dosing recommendations. METHODS: Levetiracetam, lacosamide, and phenytoin CRRT clearance was evaluated using the Prismaflex CRRT system and M150 hemodiafilters using an albumin containing normal saline (ALB-NS) vehicle with 3 different albumin concentrations (2 g/dL, 3 g/dL, and 4 g/dL) and a human plasma vehicle at 3 different effluent flow rates (1 L/hr, 2 L/hr, and 3 L/hr). Blood and effluent/dialysate concentrations were collected after circuit priming. ECs were calculated for each drug, modality, vehicle, and experimental arm combination. RESULTS: The calculated average EC for levetiracetam and lacosamide was approximated to the fraction unbound from plasma protein. Human plasma and ALB-NS vehicles demonstrated adequate prediction of in-vivo CRRT clearance. Geometric mean ratios indicated similarity in extraction coefficients when comparing between hemofiltration and hemodiafiltration modalities and between filtration and dialysis modalities at effluent flow rates ≤ 2L/hr. Evaluation of phenytoin provided inconsistent findings with regards to extraction coefficient similarity across different CRRT modalities. CONCLUSION: The findings indicate that an ex-vivo study can be used as a surrogate to predict in-vivo levetiracetam and lacosamide clearance in patients receiving CRRT.

Development of a Novel Gastric Process Simulation Model: The Successful Assessment of Bioequivalence and Bioinequivalence of a Biopharmaceutics Classification System Class II Weak Acid Drug.

Bioequivalence has been assessed using in vitro dissolution testing, such as in vivo predictive dissolution methodology. However, the assessment of bioequivalence should be performed carefully, considering the effect of the in vivo environment and according to the properties of the drug. The gastric emptying process is a key factor for the assessment of biopharmaceutics classification system class II (BCS class IIa) drugs with acidic properties since they cannot dissolve in the acidic stomach, but do dissolve in the small intestine (SI). The disintegration of a tablet in the stomach affects the distribution/dissolution in the SI due to the difference in the gastric emptying step, which in turn is a result of the varying formulation of the drugs. In this study, we used the reported dynamic pH change method and a novel gastric process simulation (GPS) model, which can compare the gastric emptying of particular-sized drug particles. The in vitro results were compared to clinical data using bioequivalent and bioinequivalent products of candesartan cilexetil. It was revealed that the dynamic pH change method was inappropriate, whereas the amount of filtered drug in GPS studies with 20 and 50 µm pore size filters could reflect the clinical results of all products. The evaluation of the gastric emptying process of drug particles less than 50 µm enabled us to assess the bioequivalence because they probably caused the difference in the distribution in the SI. This study demonstrated the utility of the GPS model for the assessment of bioequivalence of BCS class IIa drugs.

Drug clearance by aldehyde oxidase: can we avoid clinical failure?

Despite increased awareness of aldehyde oxidase (AO) as a major drug-metabolising enzyme, predicting the pharmacokinetics of its substrates remains challenging. Several drug candidates have been terminated due to high clearance, which were subsequently discovered to be AO substrates. Even retrospective extrapolation of human clearance, from models more sensitive to AO activity, often resulted in underprediction.The questions of the current work thus were: Is there an acceptable degree of in vitro AO metabolism that does not result in high in vivo human clearance? And, if so, how can this be predicted?We built an in vitro/in vivo correlation using known AO substrates, combining multiple in vitro parameters to calculate the blood metabolic clearance mediated by AO (CLbAO). This value was compared with observed blood clearance (CLb-obs), establishing cut-off CLbAO values, to discriminate between low and high CLb-obs. The model was validated using additional literature compounds, and CLb-obs was predicted in the correct category.This simple, categorical, semi-quantitative yet multi-factorial model is readily applicable in drug discovery. Further, it is valuable for high-clearance compounds, as it predicts the CLb group, rather than an exact CLb value, for the substrates of this poorly-characterised enzyme.

Applications of bio-predictive dissolution tools for the development of solid oral dosage forms: current industry experience.

Development and optimization of orally administered drug products often require bio-predictive tools to help with informing formulation and manufacturing decisions. Reliable bio-predictive dissolution toolkits not only allow rational development of target formulations without having to conduct excessive in vivo studies but also help in detecting critical material attributes (CMAs), critical formulation variables (CFVs), or critical process parameters (CPPs) that could impact a drug's in vivo performance. To provide early insights for scientists on the development of a bio-predictive method for drug product development, this review summarizes current phase-appropriate bio-predictive dissolution approaches applicable to address typical concerns on solubility-limited absorption, food effect, achlorhydria, development of extended-release formulation, clinically relevant specification, and biowaiver. The selection of an in vitro method which can capture the key rate-limiting step(s) of the in vivo dissolution and/or absorption is considered to have a better chance to produce a meaningful in vitro-in vivo correlation (IVIVC) or in vitro-in vivo relationship (IVIVR).

Using Tiny-TIM Dissolution and In Silico Simulation to Accelerate Oral Product Development of a BCS Class II Compound.

Though oral drug delivery is the most preferred route of administration, there is high drug pharmacokinetic variability associated with the oral route. Change in drug substance particle size distribution, formulation composition, or manufacturing process may impact the dissolution and, hence, the systemic drug absorption in biopharmaceutics classification system class II compounds. In the present research, using a Boehringer Ingelheim investigational drug substance as the model compound, the tiny-TIM in vitro data and in silico pharmacokinetic model were used to establish in vitro-in vivo correlation and to predict the oral bioavailability. The level C in vitro-in vivo correlation between in vivo AUC and in vitro amount dissolved in both fasted and fed states could be established. Furthermore, level A in vitro-in vivo correlation was established between in vivo fraction absorbed and bioaccessibility from tiny-TIM dissolution in both fasted and fed states. Prediction of positive food effect from tiny-TIM dissolution was consistent with conclusion from clinical studies. Such predictive models developed using the minimum clinical data and the in vitro tiny-TIM data have the potential to reduce the animal and human experiments and to expedite the overall drug development process.

IVIVC of Octreotide in PLGA-Glucose Microsphere Formulation, Sandostatin® LAR.

In vitro-in vivo correlation (IVIVC) analysis reveals a relationship between in vitro release and in vivo pharmacokinetic response of the drug of interest. Sandostatin LAR Depot (SLD) for endocrine tumors and acromegaly is a sustained-release formulation of octreotide, a cyclic oligomer of 8 amino acids, which prolongs therapeutic efficacy and enhances medication compliance of octreotide. Since the efficacy of SLD is dependent on the pharmacokinetic characteristics of octreotide released from a biodegradable matrix polymer, poly(lactide-co-glycolide)-glucose, of SLD, the IVIVC of SLD is critical for predicting an in vivo behavior of the octreotide. In this study, in vitro release of octreotide from SLD was investigated using the release test media each containing 0.02% or 0.5% surfactant and having different pH values of 7.4 and 5.5. In vivo pharmacokinetic profiles of SLD were determined by LC-MS/MS analysis of the systemic blood concentration of octreotide after the SLD injection to rodents. In IVIVC analysis, the Weibull model was adopted as a drug release model for biodegradable microsphere formulation. The IVIVC analyses revealed the in vitro release test condition of SLD with the highest IVIV correlation coefficient. By applying the in vitro release data to the model derived from the IVIVC analysis, pharmacokinetic parameters of SLD could be predicted with the prediction error of ± 10 ~ 15%. IVIVC analysis and pharmacokinetic prediction model of SLD in our study can be an efficient tool for the development of long-acting pharmaceutical dosage forms.