Viscosity Reduction and Stability Enhancement of Monoclonal Antibody Formulations Using Derivatives of Amino Acids

Srivastava, Arvind K.; O'Dell, Courtney; Bolessa, Evon; McLinden, Suman; Fortin, Lori; Deorkar, Nandkumar

doi:10.1016/j.xphs.2022.05.011

Cited by 9 publications

(5 citation statements)

References 33 publications

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“… 9 Of 34 US Food and Drug Administration (FDA)-approved DPs with high mAb concentration, 17 use salts or amino acids as excipients, likely with the aim to reduce PPIs and thus lower mAb solution viscosity. 10 More explorative excipients with demonstrated potential for viscosity reduction are poly-l-glutamic acid, 11 caffeine, 12 hydrophobic salts, 13 or amino acid derivates, 14 but no application in commercialized drug products exists due to lack of approval as excipients for parenteral administration or concerns on toxicity.…”

Section: Introductionmentioning

confidence: 99%

Predictive modeling of concentration-dependent viscosity behavior of monoclonal antibody solutions using artificial neural networks

Schmitt

Razvi

Grapentin

2023

mAbs

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Solutions of monoclonal antibodies (mAbs) can show increased viscosity at high concentration, which can be a disadvantage during protein purification, filling, and administration. The viscosity is determined by protein-protein-interactions, which are influenced by the antibody’s sequence as well as solution conditions, like pH, buffer type, or the presence of salts and other excipients. To predict viscosity, experimental parameters, like the diffusion interaction parameter (kD), or computational tools harnessing information derived from primary sequence, are often used, but a reliable predictive tool is still missing. We present a modeling approach employing artificial neural networks (ANNs) using experimental factors combined with simulation-derived parameters plus viscosity data from 27 highly concentrated (180 mg/mL) mAbs. These ANNs can be used to predict if mAbs exhibit problematic viscosity at distinct concentrations or to model viscosity-concentration-curves.

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Section: Introductionmentioning

confidence: 99%

Predictive modeling of concentration-dependent viscosity behavior of monoclonal antibody solutions using artificial neural networks

Schmitt

Razvi

Grapentin

2023

mAbs

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“…Arginine can also shield antibody hydrophobic interactions, enhancing its viscosity-reducing function. Other excipients with analogous effects are caffeine, hydrophobic salts, or amino acid derivatives, but they are not yet employed in commercialized drug products. Addition of viscosity-reducing pharmaceutical excipients to mAb formulations is indeed a common practice and also the subject of continuous research. − …”

Section: Introductionmentioning

confidence: 99%

Biophysical Determinants for the Viscosity of Concentrated Monoclonal Antibody Solutions

Mosca,

Pounot,

Beck

et al. 2023

Mol. Pharmaceutics

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Monoclonal antibodies (mAbs) are particularly relevant for therapeutics due to their high specificity and versatility, and mAb-based drugs are hence used to treat numerous diseases. The increased patient compliance of self-administration motivates the formulation of products for subcutaneous (SC) administration. The associated challenge is to formulate highly concentrated antibody solutions to achieve a significant therapeutic effect, while limiting their viscosity and preserving their physicochemical stability. Protein−protein interactions (PPIs) are in fact the root cause of several potential problems concerning the stability, manufacturability, and delivery of a drug product. The understanding of macroscopic viscosity requires an in-depth knowledge on protein diffusion, PPIs, and self-association/aggregation. Here, we study the self-diffusion of different mAbs of the IgG1 subtype in aqueous solution as a function of the concentration and temperature by quasi-elastic neutron scattering (QENS). QENS allows us to probe the short-time self-diffusion of the molecules and therefore to determine the hydrodynamic mAb cluster size and to gain information on the internal mAb dynamics. Small-angle neutron scattering (SANS) is jointly employed to probe structural details and to understand the nature and intensity of PPIs. Complementary information is provided by molecular dynamics (MD) simulations and viscometry, thus obtaining a comprehensive picture of mAb diffusion.

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“…In general, ingredients such as salts, amino acids, sugars, polyols or surfactants are added to the formulations to overcome these phenomena. In this context, bis-acetyl-lysine and propionyl serine have been identified as more efficient agents compared to the commonly used excipients to minimize the antibody solution viscosity while preventing protein–protein interactions [ 108 ].…”

Section: Stability Of Anticancer Monoclonal Antibodymentioning

confidence: 99%

Anticancer Drugs: Recent Strategies to Improve Stability Profile, Pharmacokinetic and Pharmacodynamic Properties

et al. 2022

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In past decades, anticancer research has led to remarkable results despite many of the approved drugs still being characterized by high systemic toxicity mainly due to the lack of tumor selectivity and present pharmacokinetic drawbacks, including low water solubility, that negatively affect the drug circulation time and bioavailability. The stability studies, performed in mild conditions during their development or under stressing exposure to high temperature, hydrolytic medium or light source, have demonstrated the sensitivity of anticancer drugs to many parameters. For this reason, the formation of degradation products is assessed both in pharmaceutical formulations and in the environment as hospital waste. To date, numerous formulations have been developed for achieving tissue-specific drug targeting and reducing toxic side effects, as well as for improving drug stability. The development of prodrugs represents a promising strategy in targeted cancer therapy for improving the selectivity, efficacy and stability of active compounds. Recent studies show that the incorporation of anticancer drugs into vesicular systems, such as polymeric micelles or cyclodextrins, or the use of nanocarriers containing chemotherapeutics that conjugate to monoclonal antibodies can improve solubility, pharmacokinetics, cellular absorption and stability. In this study, we summarize the latest advances in knowledge regarding the development of effective highly stable anticancer drugs formulated as stable prodrugs or entrapped in nanosystems.

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Viscosity Reduction and Stability Enhancement of Monoclonal Antibody Formulations Using Derivatives of Amino Acids

Cited by 9 publications

References 33 publications

Predictive modeling of concentration-dependent viscosity behavior of monoclonal antibody solutions using artificial neural networks

Predictive modeling of concentration-dependent viscosity behavior of monoclonal antibody solutions using artificial neural networks

Biophysical Determinants for the Viscosity of Concentrated Monoclonal Antibody Solutions

Anticancer Drugs: Recent Strategies to Improve Stability Profile, Pharmacokinetic and Pharmacodynamic Properties

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