Comment on "In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically-Based Absorption Models"

Supersaturation and Precipitation Applicated in Drug Delivery Systems: Development Strategies and Evaluation Approaches

Supersaturation is a promising strategy to improve gastrointestinal absorption of poorly water-soluble drugs. Supersaturation is a metastable state and therefore dissolved drugs often quickly precipitate again. Precipitation inhibitors can prolong the metastable state. Supersaturating drug delivery systems (SDDS) are commonly formulated with precipitation inhibitors, hence the supersaturation is effectively prolonged for absorption, leading to improved bioavailability. This review summarizes the theory of and systemic insight into supersaturation, with the emphasis on biopharmaceutical aspects. Supersaturation research has developed from the generation of supersaturation (pH-shift, prodrug and SDDS) and the inhibition of precipitation (the mechanism of precipitation, the character of precipitation inhibitors and screening precipitation inhibitors). Then, the evaluation approaches to SDDS are discussed, including in vitro, in vivo and in silico studies and in vitro-in vivo correlations. In vitro aspects involve biorelevant medium, biomimetic apparatus and characterization instruments; in vivo aspects involve oral absorption, intestinal perfusion and intestinal content aspiration and in silico aspects involve molecular dynamics simulation and pharmacokinetic simulation. More physiological data of in vitro studies should be taken into account to simulate the in vivo environment. The supersaturation theory should be further completed, especially with regard to physiological conditions.

Further Considerations Towards an Effective and Efficient Oncology Drug Discovery DMPK Strategy

BACKGROUND

DMPK data and knowledge are critical in maximising the probability of developing successful drugs via the application of in silico, in vitro and in vivo approaches in drug discovery.

METHODS

The evaluation, optimisation and prediction of human pharmacokinetics is now a mainstay within drug discovery. These elements are at the heart of the 'right tissue' component of AstraZeneca's '5Rs framework' which, since its adoption, has resulted in increased success of Phase III clinical trials. With the plethora of DMPK related assays and models available, there is a need to continually refine and improve the effectiveness and efficiency of approaches best to facilitate the progression of quality compounds for human clinical testing.

RESULTS

This article builds on previously published strategies from our laboratories, highlighting recent discoveries and successes, that brings our AstraZeneca Oncology DMPK strategy up to date. We review the core aspects of DMPK in Oncology drug discovery and highlight data recently generated in our laboratories that have influenced our screening cascade and experimental design. We present data and our experiences of employing cassette animal PK, as well as re-evaluating in vitro assay design for metabolic stability assessments and expanding our use of freshly excised animal and human tissue to best inform first time in human dosing and dose escalation studies.

CONCLUSION

Application of our updated drug-drug interaction and central nervous system drug exposure strategies are exemplified, as is the impact of physiologically based pharmacokinetic and pharmacokinetic-pharmacodynamic modelling for human predictions.

In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing

Purpose: To review in vitro testing and simulation platforms that are in current use to predict in vivo performances of generic products as well as other situations to provide evidence for biowaiver and support drug formulations development. Methods: Pubmed and Google Scholar databases were used to review published literature over the past 10 years. The terms used were “simulation AND bioequivalence” and “modeling AND bioequivalence” in the title field of databases, followed by screening, and then reviewing. Results: A total of 22 research papers were reviewed. Computer simulation using software such as GastroPlus™, PK-Sim^® and SimCyp^® find applications in drug modeling. Considering the wide use of optimization for in silico predictions to fit observed data, a careful review of publications is required to validate the reliability of these platforms. For immediate release (IR) drug products belonging to the Biopharmaceutics Classification System (BCS) classes I and III, difference factor (ƒ₁) and similarity factor (ƒ₂) are calculated from the in vitro dissolution data of drug formulations to support biowaiver; however, this method can be more discriminatory and may not be useful for all dissolution profiles. Conclusions: Computer simulation platforms need to improve their mechanistic physiologically based pharmacokinetic (PBPK) modeling, and if prospectively validated within a small percentage of error from the observed clinical data, they can be valuable tools in bioequivalence (BE) testing and formulation development.

In silico (computed) modelling of doses and dosing regimens associated with morphine levels above international legal driving limits

BACKGROUND

Morphine can cause central nervous system side effects which impair driving skills. The legal blood morphine concentration limit for driving is 20 µg/L in France/Poland/Netherlands and 80 µg/L in England/Wales. There is no guidance as to the morphine dose leading to this concentration.

AIM

The in silico (computed) relationship of oral morphine dose and plasma concentration was modelled to provide dose estimates for a morphine plasma concentration above 20 and 80 µg/L in different patient groups.

DESIGN

A dose-concentration model for different genders, ages and oral morphine formulations, validated against clinical pharmacokinetic data, was generated using Simcyp^®, a population-based pharmacokinetic simulator.

SETTING/PARTICIPANTS

Healthy Northern European population parameters were used with age, gender and renal function being varied in the different simulation groups. In total, 36,000 simulated human subjects (100 per modelled group of different ages and gender) received repeated simulated morphine dosing with modified-release or immediate-release formulations.

RESULTS

Older age, women, modified-release formulation and worse renal function were associated with higher plasma concentrations. Across all groups, morphine doses below 20 mg/day were unlikely to result in a morphine plasma concentration above 20 µg/L; this was 80 mg/day with the 80 µg/L limit.

CONCLUSION

This novel study provides predictions of the in silico (computed) dose-concentration relationship for international application. Individualised morphine prescribing decisions by clinicians must be informed by clinical judgement considering the individual patient's level of impairment and insight irrespective of the blood morphine concentration as people who have impaired driving will be breaking the law. Taking into account expected morphine concentrations enables improved individualised decision making.

Reply to "Comment on 'In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models'"

This is a reply to the comment on "In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models" by Turner and other Simcyp associates. In the reply we address the major concerns raised by Turner et al. regarding the methodology to compare the predictive performance of the different absorption models and at the same time ensure that the systemic pharmacokinetic input was exactly the same for the different models; the selection of the human effective permeability value of fexofenadine; the adoption of model default values and settings; and how supersaturation/precipitation was handled. In addition, we also further discuss aspects related to differences in in silico models and the potential implications of such differences. Our original report should be viewed as the starting point in a thorough and transparent review of absorption prediction models with the overall aim of improving their application as validated tools for bridging studies of active pharmaceutical ingredients from various sources and origins in a regulatory context. With this reply we encourage other independent investigators to perform further model evaluations of commercial as well as other existing or recently implemented models. This will boost the overall progression of physiologically based biopharmaceutical models for predicting and simulating intestinal drug absorption both in research and development and in a regulatory context.