A Review on IVIVC in The Development of Oral Drug Formulation:

Data Obtained from Past Two Decades

 

Sirisha. S

Sree Venkatsewara University of Pharmaceutical Sciences, Tirupathi, Chitoor (Dis).

 

ABSTRACT:

Rapidity in Drug development can be achieved by researchers on finding a mathematical link between bioavailability and dissolution testing which leads to the concept of in vitro - in vivo correlation (IVIVC). This review article aimed to assess papers published in the last two decades regarding the use of the IVIVC in the development of oral formulations. A systematic search was done to retrieve articles reporting the use of the IVIVC in the oral formulation development in the period from 2000 to2020. The qualified studies were abstracted regarding the Biopharmaceutical Classification System (BCS)that explains the suitability of IVIVC, drug name, dosage form number of formulations, presence of the validation and predictability. The discussion was supported by these data, which allowed to address broadly strengths and weaknesses in thisarea. Moreover, a large database has been described in this article containing different IVIVC models, with different substances, providing support to scientists interested in this area.

 

 

 

1. INTRODUCTION:

To reduce the time for approval of a new pharmaceutical product, reduce the cost of development to maximize the return on investment, and to improve the access of the patients, pharmaceutical industry and regulatory agencies are working continuously around the world wide. To achieve a more rational and assertive development flow, pharmaceutical industry has experimented and adopted several strategies and multidisciplinary approaches over the last two decades. In the development of oral drug formulations, these efforts were mainly in the use of tools such as Quality by Design (QbD) (1,2), Design of Experiments (DoE) (3), In vitro – In vivo Correlation (IVIVC) (4), and the use of the Biopharmaceutical Classification System (BCS).

 

The development and optimization of a pharmaceutical product involves various levels such as selection of excipients, processes, manufacturing equipment, development and validation of analytical methods to assess the in vitro performance and quality attributes, as well as expensive in vivo studies to asses efficacy and safety (2). Considering that quantitative and/or qualitative changes in a formulation may affect drug release and its performance in vivo, impacting directly on its efficacy and safety (5). Moreover, with ever increasing pressures to reduce the timeline of product development, it is necessary an integrated work of scientists from the analytical, clinical and other pharma teams to ensure the success of pharmaceutical products in all stages of the development.

 

In this context, IVIVC has been used as a powerful tool for establishing a rational relationship between in vitro and in vivo characteristics. By definition, IVIVC is a predictive mathematical model describing the relationship between an in vitro property of a dosage form (usually the rate or extent of drug dissolution or release) and a relevant in vivo response, e.g. plasma drug concentration or amount of drug absorbed (6,4,7). In vitro release is generally represented by dissolution profiles in bio relevant and/or bio-predictive media, and in vivo release is provided generally by pharmacokinetic studies. IVIVC constitutes an integral part of the development of a drug product, mainly for modified-release (MR) formulations, aiming to optimize prototypes, set dissolution limits, reduce the number of bioequivalence studies during the development and to support post-approval changes (components or composition, manufacturing site, scale-up/scale-down, manufacturing process or equipment) (8). Thus, the objective of this work was to assess how this tool has been used by scientists in the context of oral drug formulation development. For this purpose, papers published in the period from 2000 to 2019 related to the use of the IVIVC in the development of oral formulations were retrieved to compose a significant sample and demonstrate the scenario in this research field. Finally, this article provides a large compilation of information on different drugs regarding the application of IVIVC, and it may be consulted by scientists interested in this approach for oral formulation development.

 

2. ANALYSIS OF ARTICLES AND DATA EXTRACTION:

The included articles were analyzed, and the following data extracted: drug/substance name, dosage form, BCS class of drug (when available in the article or consulted in the Drug Delivery Foundation database (available in http://www.ddfint.org/bcs-about), in vitro and in vivo data used for IVIVC, IVIVC level, number of formulations used in IVIVC, and presence of validation and predictability of IVIVC (internal and/or external predictions). Table 1 represents the data obtained from various databases and articles from 2000-2020.

 

Table:1 All relevant information from the articles and database.

 

AUC: area under the curve, BCS: biopharmaceutics classification system,

Cmax: maximum plasma concentration,

CR: controlled release, ER: extended-release,

FaSSIF: fasted state simulated intestinal fluid,

FeSSIF: fed state simulated intestinal fluid,

HPMC: hydroxypropyl methyl cellulose,

IR: immediate-release,

IVIVC: in vitro – in vivo correlation,

MR: modified-release, MDT: mean dissolution time,

MRT: mean residence time,

NA: not applied, ND: not described,

PE: prediction error, PK: pharmacokinetic,

SDS: sodium dodecyl sulfate,

SGF: simulated gastric fluid,

SIF: simulated intestinal fluid, SR: sustained-release,

T50% (or TXX%): time to reach 50% (or XX%) of dissolution, USP: United States Pharmacopoeia.

Tmax: time to reach maximum plasma concentration,

 

To demonstrate all relevant information from the included articles, table 1 was designed to present the following data: name of drug/substance, dosage form, BCS class of drug, in vitro and in vivo data used for IVIVC, methodology applied for dissolution test or other used to assess the in vitro characteristics, deconvolution method used to obtain fraction absorbed (when applied), in vivo study design and population, IVIVIC level achieved (A, B, C, multiple C or D), number of formulations applied in the IVIVC and presence or absence of validation (internal and/or external) and predictability.

 

3. Dosage form and Biopharmaceutics Classification System:

Oral route is the most frequently used way of drug administration, as well as the most convenient, economic and preferred by patient (15). MR dosage forms are formulated to achieve a desired therapeutic objective or better patient compliance. Types of MR drug products include delayed-release (DR) (e.g. enteric-coated), extended-release (ER or XR), sustained-release (SR), controlled-release (CR), and others (15,16). These definitions may have slight variations between countries and regulatory agencies.

 

Biopharmaceutics classification system (BCS) is often used to predict the in vivo behavior of oral formulations, essentially based on drug solubility and intestinal permeability extension (17). BCS class I drugs are highly permeably and soluble substances; therefore, they depend only on the release rate of the dosage form for dissolution on the gastro-intestinal (GI) fluids and, then, permeate intestinal or stomach mucosae. For a BCS class I drug contained in an IR dosage form, gastric emptying is the only limiting factor for drug absorption, which would not enable prediction of the in vivo behavior based on in vitro assays. Therefore, for this case, the acronym “IVIVC” (quantitative correlations) is inappropriate and the other acronym, as IVIVR (in vitro in vivo relationship – qualitative correlations), should be considered, since this approach only provides a formulation rank order based on dissolution profiles, and is not useful for regulatory purposes. In general, IVIVC for IR dosage forms is more difficult to be achieved (18,7).

 

In addition to BCS class I, in the group of highly permeable substances, BCS class II are drugs with good permeability but with poor solubility. Thus, in this case, the dosage form plays a key role to improve drug solubility and to control the release rate to promote the best condition for dissolution and, consequently, permeability. Sub-classifications for BCS class II have been proposed recently (IIa, IIb and IIc) (19), since these substances are highly dependent on the characteristics of the drug in the physiological pH range (acidic, basic or neutral drugs), formulation factors and luminal environment (e.g. presence of food). This approach considers BCS class IIa as weak acid drugs, with good solubility in the small intestine and low solubility in the acidic stomach pH, while BCS class IIb is the classification for weak base drugs with low solubility in the small intestine and good solubility in the acidic stomach pH. Finally, BCS by the physiological pH range(19).

 

BCS classes III and IV drugs are poorly permeable, and this is related to molecule characteristics, with no regard to the formulation. Thereby, for these classes, any in vitro simulation aimed at predicting the in vivo behavior is generally more difficult or limited. On the other hand, since only the dissolved drug in luminal fluids may permeate the mucosa at the absorptive sites of the GI tract, both the solubility of the drug and the release/dissolution rate of the dosage form are crucial for the in vivo input rate. Considering that release/dissolution is a limiting factor able to be simulated through in vitro tests (e.g. dissolution profiles), an IVIVC successful is expected mainly for BCS classes I and II, since for these classes drug permeability is not a limiting factor (20). In this sense, table 2 describes a relationship regarding the dosage form and probability to obtain a powerful IVIVC for each BCS class.

 

Table.2. Relationship between dosage form, BCS class and IVIVC probability

MR: modified release; BCS: biopharmaceutics classification system. IVIVC: in vitro in vivo correlation.

MR dosage form has been the most applicable (54%) for IVIVC approaches, considering the articles assessed. In consensus with the IVIVC theoretical concepts (18,20,4), BCS classes I (34%) and II (46%) have been the most usual classes used for IVIVC. In general, the articles assessed demonstrated that high permeability (BCS class I and II) drugs have been the main class applied for IVIVC approaches for oral dosage form intended to drug absorption in GI tract, it is common to use dissolution media within the pH range of 1.2 - 6.8 to simulate the GI environment (stomach and intestine portions). Fasting and fed states also are important to set the adequate pH and dissolution media components (e.g. enzymes, salts, etc.) necessary to simulate these conditions. In addition, in the fed state, the delayed intragastrical dissolution caused by some food components may affect the absorption rates of drugs (especially poorly soluble drugs) and, subsequently, may influence its pharmacokinetics compared to the fasted state (21,22).

 

In this way, bio-relevant and bio-predictive dissolution media for simulating stomach and small intestine, as well as conditions before and after meals, have been developed. The following examples may be cited: Simulated Gastric Fluid (SGF), Simulated Intestinal Fluid (SIF), Fasted State Simulated Intestinal Fluid (FaSSIF) and Fed State Simulated Intestinal Fluid (FeSSIF) (23).

 

Among the retrieved articles, it was observed that the dissolution media in physiological pH range have been used as a single step or varying pHs in order to simulate different parts of GI tract (multiple steps). Single step dissolution medium was found to be (48%), while multiple steps approach was related upto (26%). Bio-predictive/bio-relevant media (SGF, SIF, FaSSIF and FeSSIF) is (20%) and water medium was related about (6%).

 

Many articles have been published with different approaches regarding dissolution media and apparatuses to find the adequate condition to simulate the in vivo behavior for an oral dosage form and to expose the dosage form to an environment potentially closer to that of the GI tract USP III (reciprocating cylinder) and USP IV (flowthrough cell) would be used (24,25,26). USP IV has been widely recommended for poorly soluble drugs (27), MR tablets (28), and medical devices. Additionally, in the last years, nonconventional, custom-made and specific apparatuses have been developed to improve IVIVC approaches. A multi-compartmental model TNO GI realistically simulate conditions of the GI tract based on a computer simulation of the digestive conditions, is an example that demonstrates the advance of the dissolution apparatus. Some systems have included a second stage in the apparatus, using an organic solvent or a membrane, for simulating the absorption process in the small intestine (29). Among the articles retrieved, the USP II (paddle) apparatus was the most applicable in the IVIVC studies assessed (52%) as shown in figure 1. Non-conventional or custom-made apparatuses were used in 24%, followed by USP I (basket) in 14%, USP IV (flow-through cell) in 6% and USP III (reciprocating cylinder) in 2%.

 

Figure 1. Percentage distribution of dissolution apparatuses applied in the IVIVC studies retrieved (N = 50).

 

4. In vitro data:

To study the in vitro release kinetics of a dosage form, it is recommended that data obtained from in vitro drug release studies have results at least 85% of drug released/dissolved, sufficient number of points to elucidate the dissolution curve shape. By using these data it is possible to plot dissolution rate profile cures to characterize the rate of drug release/dissolution is possible by using a mathematical model. Moreover, for IVIVC purposes, in cases where the timepoints of dissolution profile are not calculated in other timepoints to construct a point-to-point relationship. Other Mathematical models such as Weibull, Higuchi, Korsemeyer-peppas among others, are usually applied for dissolution profile modeling (30,31).

 

In conclusion, based on IVIVC studies assessed for oral formulations, the main in vitro parameter, which has been used to correlate with in vivo, is the fraction dissolved obtained from dissolution tests. This type of correlation seeks to establish a link between in vitro and in vivo dissolution, which would be directly related to the in vivo input rate of a drug, mainly for highly permeable substances.

 

4.1. In vivo data:

Pharmacokinetic studies are the way to elucidate the behavior of a drug in the body when administered through a dosage form (32). Adequate sample size, design, population, and bioanalytical method are fundamental characteristics to perform a pharmacokinetic study and to have useful data. Subjects should be standardized as much as possible and acceptable to minimize intra and inter individual variation (33,34).

 

Generally, concentration-time profile generated from a pharmacokinetic study is treated previously to the IVIVC approach to relate directly to the in vitro release rate. First, in vivo data are converted to fraction of dose absorbed or fraction absorbed ‘Fa’, to have the “pure” absorption process and, consequently, to be possible correlate directly with in vitro release (fraction dissolved). In other words, it is necessary to “remove” the elimination process of the absorption curve (initial phase after administration), since the in vitro assay (e.g. dissolution test) does not predict the in vivo elimination rate of a drug. For oral formulations, the traditional deconvolution/convolution-based approach is the most common methodology to establish an IVIVC level A. Wagner–Nelson (Wagner and Nelson, 1964) and Loo-Riegelman (Wagner, 1975) are model-dependent methods based on one and two compartments, respectively. Wagner-Nelson has the great advantage of not requiring additional in vivo data beyond oral plasma profile, while the Loo–Riegelman method requires intravenous dosing data. Numerical deconvolution is a model-independent method that requires in vivo plasma data from an oral solution, or intravenous, as the unit impulse response, UIR. All three methods have limitations, but the requirement of additional data in addition to oral plasma data (from tablet or capsule) significantly limits the application of the Loo- Riegelman and numerical deconvolution methods (35,36). Wagner-Nelson, Loo-Riegelman and numerical deconvolution are considered conventional methods and widely applied for IVIVC models.

 

Among the IVIVC studies assessed (N = 50), the most frequently applied model for deconvolution was Wagner- Nelson model has been widely applied for IVIVC purposes

 

4.2. IVIVC level, number of formulations, validation and predictability:

Levels A, B, and C IVIVC are clearly defined in some regulatory guidelines (37,7). Level A, as a point-to-point correlation, represents the most informative class of 7), an IVIVC may be defined with a minimum of two formulations with different release rates (e.g. highest and lowest release rate formulations); three or more formulations with different release rates are recommended. In addition, the IVIVC should be evaluated to demonstrate its capacity to predict the in vivo performance of an oral drug formulation based on its in vitro dissolution characteristics and whether this model is maintained over a range of in vitro dissolution release rates and manufacturing Predictability may be evaluated in two ways: internally or externally, depending on the intended application. Internal predictability is based on the initial data used to define the IVIVC model; in other words, it is based on a retrospective calculation of initial data. Differently, external predictability is assessed when an additional formulation (new dataset) is applied in the IVIVC model established (20).

 

In general, the combination of both internal and external assessments is recommended, For product development, to choose the best prototype for bioequivalence study, Cmax and AUC are essential parameters for testing IVIVC predictability. Moreover, these parameters must be assessed and established when IVIVC is applied for biowaiver in post-approval changes. Both internal and external predictabilities must be assessed after convolution process (application of in vitro data on IVIVC to obtain plasma concentration profile predicted), comparing the data observed versus data predicted. Average absolute percent prediction error (PE) between observed and predicted must not exceed 10% and individual PE for each formulation must not exceed 15%. If these criteria are not met, IVIVC is considered inconclusive, and should not be considered a surrogate for bioequivalence (7)

 

5. CONCLUSION:

Recent advances in the development of new methodologies that mimic GI conditions or other regions of the body has been observed, mainly with the development of multi-compartmental apparatuses that simulate environments and processes concomitantly (disintegration, dissolution and permeation). In the same sense, mathematical models for modeling have been implemented in the field of pharmacokinetics to create algorithms and applications in extrapolation of data to other populations or in specific pathological condition. In this context, IVIVC is currently supported by several tools that allow advancing in data correlation, as well as mimicking more accurately the conditions in vivo from in vitro assays/technologies.

 

Despite the observed advances of these tools, the sample of articles extracted from the two databases used in this review demonstrated that there are still very few published works with advanced technologies and that the application has been mainly in the early stage, and not for regulatory purposes. The following highlights have been described, based on discussion session, to summarize the main findings observed in the articles assessed:

·       MR dosage form has been the most applicable (54%) for IVIVC approaches;

·       BCS classes I and II have been the most classes used for IVIVC;

·       USP II (paddle) was the most (52%) applicable apparatus for IVIVC purposes;

·       70% of the IVIVC studies assessed used dissolution profile data, specifically fraction dissolved, for IVIVC approaches;

·       Wagner-Nelson is the most frequently applied deconvolution model for IVIVCs (26 of 50 IVIVC studies);

·       78% of the IVIVC studies assessed did not show any validation and/or predictability data to prove the applicability of the IVIVC model

 

The last two years (2017 – 2018) of the period searched showed a significant growth in the number of publications of IVIVC studies for oral formulations.

 

Data analysis from retrieved articles showed the main characteristics of the studies, such as applied mathematical models, apparatus, main BCS classes, dosage forms, in vivo and in vitro models, among others. A discussion was completed based on these data, which allowed to address strengths and weaknesses in this area in a broad, comprehensive fashion.

 

Finally, this article contains an important screenshot of the use of IVIVC in the oral formulation development, as well as a view on trends and improvements needed in this area.

 

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Received on 12.05.2020          Modified on 26.05.2020

Accepted on 11.06.2020     ©AandV Publications All right reserved