Bridging in vitro dissolution and in vivo exposure for acalabrutinib. Part I. Mechanistic modelling of drug product dissolution to derive a P-PSD for PBPK model input

Pépin, Xavier; Sanderson, Natalie; Blanazs, Alexander; Grover, Shveta; Ingallinera, Timothy G.; Mann, James

doi:10.1016/j.ejpb.2019.07.014

Cited by 35 publications

(61 citation statements)

References 26 publications

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“…Examples of nonmechanistic integration of dissolution data are tabulated measurement of the dissolution profile over time or use of a Weibull equation or any other mathematical equation to plot drug release versus time and use that function as an input to the PBBM. Mechanistic examples for integration of dissolution including fitting a Z-factor to the dissolution data as proposed by Takano et al or the product-particle size distribution (P-PSD) approach as proposed by Pepin et al (15,17,18). Both parameters can be fitted to drug substance or drug product dissolution data.…”

Section: Mechanistic or Non-mechanistic Integrationmentioning

confidence: 99%

“…The Z-factor (volume.mass -1 .time-1 ) is a hybrid parameter function of the drug diffusion coefficient, true crystal density, thickness of the unstirred water layer, and initial particle radius. The P-PSD is a 10-bin PSD fitted to drug product dissolution data in given conditions using a modified Nernst-Brunner equation to differentiate the impact of micelles on the drug dissolution rate and define different unstirred water layer thicknesses for the free drug and micelles (17). Both the z-factor and P-PSD approaches are able to predict other dissolution conditions and therefore are independent from the dose, volume, pH, and solubility of the drug.…”

Section: Mechanistic or Non-mechanistic Integrationmentioning

confidence: 99%

“…Product batch specific dissolution data should be compared with particle size data of the drug substance used for product manufacture, because the manufacturing process and excipients may lead to changes in the drug substance surface available for dissolution. For a simple drug substance suspension it may be appropriate to utilize just the drug substance PSD as an input to the PBBM if it adequately describes the surface area, but some authors have found a disconnect between the measured PSD and the observed dissolution performance and accounted for it prior to inputting a particle size into PBBM (16,17,21). This has been described by Pepin et al with the P-PSD approach by utilizing a PSD that describes the dissolution performance of a specific batch of product, which takes into account formulationrelated dissolution rate phenomena such as wetting, disintegration, capsule rupture, and deagglomeration and integrates process parameters such as compression force or granulation time, thus providing a more accurate input to PBBM (15,17).…”

Section: Immediate-release Productsmentioning

confidence: 99%

“…The solubility of the compound in fasted state simulated intestinal fluid (the authors recommend V2) and fed state simulated intestinal fluid (authors recommend V1) alongside the blank buffers minus the bile salts and phospholipid should be measured (42,43). Depending on the PBBM platform used, a simple model using the approach proposed by Mithani et al or the fit of two partitioning coefficients for the ionized and unionized drug can be applied (17,19,44). It can also be useful to understand the apparent affinity of the drug to synthetic surfactants, as being able to predict the drug dissolution in the presence and absence of synthetic micelles is an additional verification of a mechanistic understanding of the drug dissolution.…”

Section: Reprinted From Ref 1: Journal Of Pharmaceutical Sciences Pementioning

confidence: 99%

“…If this is done the solubility in the presence of several levels of commonly used dissolution surfactants like sodium dodecyl sulfate and polysorbate 80 should be performed. It is also necessary to measure the micelle size of the surfactants to accurately predict the dissolution performance in surfactant-containing media, which typically can be measured using dynamic light scattering or obtained from the literature, if available (17,45).…”

Section: Reprinted From Ref 1: Journal Of Pharmaceutical Sciences Pementioning

confidence: 99%

See 4 more Smart Citations

The Case for Physiologically Based Biopharmaceutics Modelling (PBBM): What do Dissolution Scientists Need to Know?

Gray¹,

Mann²,

Barker³

et al. 2020

Dissolution Technol.

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The purpose of this article is to inform the dissolution scientist of a powerful emerging tool that provides in vivo linkage to dissolution methods. This tool is physiologically based biopharmaceutics modelling (PBBM). Dissolution scientists are mostly concerned with analytical sections of drug development, so exposure to modeling and other pharmacokinetics and biopharmaceutic concepts may be uncommon. PBBM is an in-silico model that focuses on the interactions between the in vivo physiology and the formulation and drug characteristics. The principles behind PBBM is that all mechanisms related to drug release, dissolution, and diffusion from the site of administration to the site of action can be described in a mechanistic way or semi-empirical way. The integration of in vitro dissolution data in PBBM is described, including examples of software and modeling applications. The expertise needed to use the software and appropriate training is discussed. The key inputs that are expected from the dissolution scientist include an understanding of the aqueous solubility across the physiological pH range, impact of in vivo relevant bile salts and phospholipids on solubilization, and the impact of surface pH on dissolution rate. An example of an advanced in vitro system, TNO intestinal model (TIM-1), will be discussed and its importance in establishing a biorelevant understanding of dissolution behavior. PBBM can evaluate the clinical relevance of a dissolution method and justify specifications and ultimately provide an approval advantage to the sponsor. A well-supported dissolution method that provides clinically relevant drug product specifications (CRDPS) will be viewed with favor by the regulators. Therefore, the partnering of a dissolution scientist and biopharmaceutics scientist to develop PBBM is clearly an important step forward in drug development.

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Section: Mechanistic or Non-mechanistic Integrationmentioning

confidence: 99%

Section: Mechanistic or Non-mechanistic Integrationmentioning

confidence: 99%

Section: Immediate-release Productsmentioning

confidence: 99%

Section: Reprinted From Ref 1: Journal Of Pharmaceutical Sciences Pementioning

confidence: 99%

Section: Reprinted From Ref 1: Journal Of Pharmaceutical Sciences Pementioning

confidence: 99%

See 3 more Smart Citations

The Case for Physiologically Based Biopharmaceutics Modelling (PBBM): What do Dissolution Scientists Need to Know?

Gray¹,

Mann²,

Barker³

et al. 2020

Dissolution Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

In Silico Prediction of Oral Drug Absorption

Dong,

Zhou,

Zheng

et al. 2023

Oral Bioavailability and Drug Delivery

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Bioequivalence and Relative Bioavailability Studies to Assess a New Acalabrutinib Formulation That Enables Coadministration With Proton‐Pump Inhibitors

Sharma

Pépin

Burri

et al. 2022

Clinical Pharm in Drug Dev

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Acalabrutinib is a Bruton tyrosine kinase (BTK) inhibitor approved to treat adults with chronic lymphocytic leukemia, small lymphocytic lymphoma, or previously treated mantle cell lymphoma. As the bioavailability of the acalabrutinib capsule (AC) depends on gastric pH for solubility and is impaired by acid‐suppressing therapies, coadministration with proton‐pump inhibitors (PPIs) is not recommended. Three studies in healthy subjects (N = 30, N = 66, N = 20) evaluated the pharmacokinetics (PKs), pharmacodynamics (PDs), safety, and tolerability of acalabrutinib maleate tablet (AT) formulated with pH‐independent release. Subjects were administered AT or AC (orally, fasted state), AT in a fed state, or AT in the presence of a PPI, and AT or AC via nasogastric (NG) route. Acalabrutinib exposures (geometric mean [% coefficient of variation, CV]) were comparable for AT versus AC (AUCinf 567.8 ng h/mL [36.9] vs 572.2 ng h/mL [38.2], Cmax 537.2 ng/mL [42.6] vs 535.7 ng/mL [58.4], respectively); similar results were observed for acalabrutinib's active metabolite (ACP‐5862) and for AT‐NG versus AC‐NG. The geometric mean Cmax for acalabrutinib was lower when AT was administered in the fed versus the fasted state (Cmax 255.6 ng/mL [%CV, 46.5] vs 504.9 ng/mL [49.9]); AUCs were similar. For AT + PPI, geometric mean Cmax was lower (371.9 ng/mL [%CV, 81.4] vs 504.9 ng/mL [49.9]) and AUCinf was higher (AUCinf 694.1 ng h/mL [39.7] vs 559.5 ng h/mL [34.6]) than AT alone. AT and AC were similar in BTK occupancy. Most adverse events were mild with no new safety concerns. Acalabrutinib formulations were comparable and AT could be coadministered with PPIs, food, or via NG tube without affecting the PKs or PDs.

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Bridging in vitro dissolution and in vivo exposure for acalabrutinib. Part I. Mechanistic modelling of drug product dissolution to derive a P-PSD for PBPK model input

Cited by 35 publications

References 26 publications

The Case for Physiologically Based Biopharmaceutics Modelling (PBBM): What do Dissolution Scientists Need to Know?

The Case for Physiologically Based Biopharmaceutics Modelling (PBBM): What do Dissolution Scientists Need to Know?

In Silico Prediction of Oral Drug Absorption

Bioequivalence and Relative Bioavailability Studies to Assess a New Acalabrutinib Formulation That Enables Coadministration With Proton‐Pump Inhibitors

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