In Vivo Stability of Therapeutic Proteins

Schuster, Joachim; Koulov, Atanas V.; Mahler, Hanns‐Christian; Detampel, Pascal; Huwyler, Jörg; Singh, Satish K.; Mathaes, Roman

doi:10.1007/s11095-019-2689-1

Cited by 51 publications

(53 citation statements)

References 141 publications

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“…17 As an alternative to serum, several studies used PBS due to its buffering capacity at pH 7.4, similar ionic strength as blood, and significantly less complex matrix to circumvent analytical challenges encountered with biological fluids. 2,5,18 While certain chemical modifications showed similar results in PBS and serum, few studies have compared physical stability in PBS to serum. 6,18 Our results provide further evidence that mAbs are less stable in serum compared to PBS in regards to protein aggregation.…”

Section: Discussionmentioning

confidence: 99%

“…SbVP formation may occur by aggregation of the therapeutic protein with endogenous biological components such as enzymes or other biological processes or due to conditions in the biological fluid driving self-aggregation. 2 To predict potential adverse effects in patients due to drug instability under physiologic conditions, stability of therapeutic proteins within the context of biological matrix is of increasing interest, especially during early stages of development and preferably prior clinical lead candidate selection. 2 Evaluation of therapeutic protein stability in biological fluids has proven challenging.…”

Section: Introductionmentioning

confidence: 99%

“…2 To predict potential adverse effects in patients due to drug instability under physiologic conditions, stability of therapeutic proteins within the context of biological matrix is of increasing interest, especially during early stages of development and preferably prior clinical lead candidate selection. 2 Evaluation of therapeutic protein stability in biological fluids has proven challenging. Conventional pharmaceutical methods for SbVP quantitation are unable to discriminate particles derived from therapeutic protein from other particles that may form in the biological fluid over incubation time.…”

Section: Introductionmentioning

confidence: 99%

“…Conventional pharmaceutical methods for SbVP quantitation are unable to discriminate particles derived from therapeutic protein from other particles that may form in the biological fluid over incubation time. 2,3 Previous reports have indicated red blood cells undergo lysis and endogenous proteins can undergo aggregation and precipitation, i.e., forming proteinaceous particles, once isolated from animals/humans. 2e6 Fluorescence methods have been applied to enable the detection of therapeutic proteins in biological fluids 3,7e10 ; however, analytical challenges remain due to the autofluorescence of biological fluid components.…”

Section: Introductionmentioning

confidence: 99%

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Assessing Particle Formation of Biotherapeutics in Biological Fluids

Schuster

Probst

Mahler

et al. 2021

Journal of Pharmaceutical Sciences

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The stability of therapeutic proteins can be impacted in vivo after administration, which may affect patient safety or treatment efficacy, or both. Stability testing of therapeutic proteins using models representing physiologic conditions may guide preclinical development strategy; however, to date only a few studies assessing the physical stability are available in the public domain. In this manuscript, the stability of seven fluorescently labeled monoclonal antibodies (mAbs) was evaluated in human serum and phosphate-buffered saline, two models often discussed to be representative of the situation in humans after intravenous administration. Subvisible particles were analyzed using light obscuration, flow imaging, and imaging flow cytometry. All methods showed that serum itself formed particles under in vitro conditions. Imaging flow cytometry demonstrated that mean particle size and counts of mAbs increased substantially in serum over five days; however, particle formation in phosphate-buffered saline was comparably low. Stability differences were observed across the mAbs evaluated, and imaging flow cytometry data indicated that fluorescently labeled mAbs primarily interacted with serum components. The results indicate that serum may be more suitable as in vitro model to simulate physiologic intravenous conditions in patients closely and evaluate the in vivo stability of therapeutic proteins. Fluorescence labeling and detection methods may be applied to differentiate particles containing therapeutic protein from high amounts of serum particles that form over time.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessing Particle Formation of Biotherapeutics in Biological Fluids

Schuster

Probst

Mahler

et al. 2021

Journal of Pharmaceutical Sciences

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“…We demonstrate the GAN library biasing on such properties as a reduction of negative surface area patches, identified as a potential source of aggregation, thermal instability, and possible half-life reductions, 51 and away from MHC class II binding, which may reduce the immunogenicity of the generated antibodies. [52][53][54][55][56] We show, additionally, library biasing to a higher isoelectric point (pI) to reduce aggregation and prevent precipitation in therapeutic formulations, and towards longer CDR3 lengths which can increase diversity and has been known to create more effective therapeutics for a class of targets.…”

Section: Introductionmentioning

confidence: 99%

Designing Feature-Controlled Humanoid Antibody Discovery Libraries Using Generative Adversarial Networks

Amimeur

Shaver

Ketchem

et al. 2020

Preprint

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We demonstrate the use of a Generative Adversarial Network (GAN), trained from a set of over 400,000 light and heavy chain human antibody sequences, to learn the rules of human antibody formation. The resulting model surpasses common in silico techniques by capturing residue diversity throughout the variable region, and is capable of generating extremely large, diverse libraries of novel antibodies that mimic somatically hypermutated human repertoire response. This method permits us to rationally design de novo humanoid antibody libraries with explicit control over various properties of our discovery library. Through transfer learning, we are able to bias the GAN to generate molecules with key properties of interest such as improved stability and developability, lower predicted MHC Class II binding, and specific complementarity-determining region (CDR) characteristics. These approaches also provide a mechanism to better study the complex relationships between antibody sequence and molecular behavior, both in vitro and in vivo . We validate our method by successfully expressing a proof-of-concept library of nearly 100,000 GAN-generated antibodies via phage display. We present the sequences and homology-model structures of example generated antibodies expressed in stable CHO pools and evaluated across multiple biophysical properties. The creation of discovery libraries using our in silico approach allows for the control of pharmaceutical properties such that these therapeutic antibodies can provide a more rapid and cost-effective response to biological threats.

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