Digitally Enabled Generic Analytical Framework Accelerating the Pace of Liquid Chromatography Method Development for Vaccine Adjuvant Formulations DOI
Mohamed Hemida, Rodell C. Barrientos,

Caleb Kinsey

et al.

ACS Pharmacology & Translational Science, Journal Year: 2024, Volume and Issue: 7(10), P. 3108 - 3118

Published: Sept. 11, 2024

The growing use of adjuvants in the fast-paced formulation new vaccines has created an unprecedented need for meaningful analytical assays that deliver reliable quantitative data from complex adjuvant and adjuvant-antigen mixtures. Due to their chemical physical properties, method development separation vaccine is considered a highly challenging laborious task. Reversed-phase liquid chromatography (RPLC) among most important tests (bio)pharmaceutical industry release stability indicating measurements including content, identity, purity profile. However, time constraints developing "on-demand" robust methods prior each change can easily lead sample analysis becoming bottleneck development. Herein, simple efficient generic framework capable chromatographically resolving commonly used non-aluminum-based across academic industrial sectors introduced. This was designed seek more proactive approach assay endeavors evolved extensive stationary phase screening conjunction with multifactorial

Language: Английский

Advances in the design and delivery of RNA vaccines for infectious diseases DOI Creative Commons
Abhijeet Lokras,

Thomas Rønnemoes Bobak,

Saahil Baghel

et al.

Advanced Drug Delivery Reviews, Journal Year: 2024, Volume and Issue: 213, P. 115419 - 115419

Published: Aug. 5, 2024

RNA medicines represent a paradigm shift in treatment and prevention of critical diseases global significance, e.g., infectious diseases. The highly successful messenger (mRNA) vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were developed at record speed during the disease 2019 pandemic. A consequence this is exceptionally shortened vaccine development times, which combination with adaptability makes technology attractive for pandemic preparedness. Here, we review state art design delivery based on different modalities, including linear mRNA, self-amplifying RNA, trans-amplifying circular RNA. We provide an overview clinical pipeline diseases, present analytical procedures, are paramount characterizing quality attributes guaranteeing their quality, discuss future perspectives using to combat pathogens beyond SARS-CoV-2.

Language: Английский

Citations

11
Optimization of recombinant antibody fragment production via machine learning models: Model development and validation DOI
Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

et al.

Process Safety and Environmental Protection, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

1
Synergistic Integration of Digital Twins and Neural Networks for Advancing Optimization in the Construction Industry: A Comprehensive Review DOI
Alexey Borovkov, Khristina Maksudovna Vafaeva, Nikolai Vatin

et al.

Construction Materials and Products, Journal Year: 2024, Volume and Issue: 7(4), P. 7 - 7

Published: Aug. 9, 2024

The object of research is the potential application digital twins and neural network modeling for optimizing construction processes. Method. Adopting a perspective approach, conducts an extensive review existing literature delineates theoretical framework integrating technologies. Insights from inform development methodologies, while case studies practical applications are explored to deepen understanding these integrated approaches system optimization. Results. yields following key findings: Digital Twins: Offer capability create high-fidelity virtual representations physical systems, enabling real-time data collection, analysis, visualization throughout project lifecycle. This allows proactive decision-making, improved constructability enhanced coordination between design field operations. Neural Network Modeling: Possesses power learn complex relationships vast datasets, predictive optimization behavior. networks can be employed forecast timelines, identify risks, optimize scheduling resource allocation. Integration Twins Networks: Presents transformative avenue processes by facilitating data-driven design, maintenance equipment infrastructure, performance monitoring. synergistic approach lead significant improvements in efficiency, reduced costs, overall quality.

Language: Английский

Citations

4
‘Applications of machine learning in liposomal formulation and development’ DOI
Sina M. Matalqah, Zainab Lafi,

Qasim Mhaidat

et al.

Pharmaceutical Development and Technology, Journal Year: 2025, Volume and Issue: 30(1), P. 126 - 136

Published: Jan. 2, 2025

Machine learning (ML) has emerged as a transformative tool in drug delivery, particularly the design and optimization of liposomal formulations. This review focuses on intersection ML technology, highlighting how advanced algorithms are accelerating formulation processes, predicting key parameters, enabling personalized therapies. ML-driven approaches restructuring development by optimizing liposome size, stability, encapsulation efficiency while refining release profiles. Additionally, integration enhances therapeutic outcomes precision-targeted delivery minimizing side effects. presents current breakthroughs, challenges, future opportunities applying to systems, aiming improve efficacy patient various disease treatments.

Language: Английский

Citations

0
In‐line prediction of viability and viable cell density through machine learning‐based soft sensor modeling and an integrated systems approach: An industrially relevant PAT case study DOI Open Access

Shivesh K. Suman,

Michaela Murr,

J. E. Crowe

et al.

Biotechnology Progress, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 23, 2025

Abstract The biopharmaceutical industry is shifting toward employing digital analytical tools for improved understanding of systems biology data and production quality products. implementation these technologies can streamline the manufacturing process by enabling faster responses, reducing manual measurements, building continuous automated capabilities. This study discusses use soft sensor models prediction viability viable cell density (VCD) in CHO culture processes using in‐line optical permittivity sensors. A significant innovation this development a simplified empirical model adoption an integrated approach prediction. initial evaluation demonstrated promising accuracy with 96% residuals within ±5% error limit Final Day mean absolute percentage ≤5% across various scales conditions. was VCD utilizing Gaussian Process Regressor Matern Kernel (nu = 0.5), selected from over hundred advanced machine learning techniques. had R 2 0.92 89% predictions ±10% significantly outperformed commonly used partial least squares regression models. results validated real‐time highlighted potential to substantially reduce reliance on labor‐intensive discrete offline measurements. integration innovative aligns regulatory guidelines establishes foundation further advancements biomanufacturing industry, control, efficiency, compliance standards.

Language: Английский

Citations

0
A Novel Paradigm on Data and Knowledge-Driven Drug Formulation Development: Opportunities and Challenges of Machine Learning DOI
Xinrui Wang,

Zhenda Liu,

Lin Xiao

et al.

Journal of Industrial Information Integration, Journal Year: 2025, Volume and Issue: unknown, P. 100796 - 100796

Published: Feb. 1, 2025

Language: Английский

Citations

0
Use of Computational Intelligence in Customizing Drug Release from 3D-Printed Products: A Comprehensive Review DOI Creative Commons
Fantahun Molla Kassa, Souha H. Youssef, Yunmei Song

et al.

Pharmaceutics, Journal Year: 2025, Volume and Issue: 17(5), P. 551 - 551

Published: April 23, 2025

Computational intelligence (CI) mimics human by expanding the capabilities of machines in data analysis, pattern recognition, and making informed decisions. CI has shown promising contributions to advancements drug discovery, formulation, manufacturing. Its ability analyze vast amounts patient optimize formulations predicting pharmacokinetic pharmacodynamic responses makes it a very useful platform for personalized medicine. The integration with 3D printing further strengthens this potential, as enables fabrication medicines precise doses, controlled-release profiles, complex formulations. Furthermore, automated digital make suitable CI. proven material printability, optimizing release rates, designing structures, ensuring quality control, improving manufacturing processes printing. In context customizing from 3D-printed products, techniques have been applied predict input variables design geometries that achieve desired profile. This review explores role It provides overview limitations printing; how can overcome these challenges, its potential release; comparison other methods optimization; real-world examples

Language: Английский

Citations

0
Digitally Enabled Generic Analytical Framework Accelerating the Pace of Liquid Chromatography Method Development for Vaccine Adjuvant Formulations DOI Creative Commons
Mohamed Hemida, Rodell C. Barrientos,

Caleb Kinsey

et al.

Published: April 15, 2024

The growing use of adjuvants in the fast-paced formulation new vaccines has created an unprecedented need for meaningful analytical assays that deliver reliable quantitative data from complex adjuvant and adjuvant-antigen mixtures. Due to their chemical physical properties, method development separation vaccine is considered a highly challenging laborious task. Reversed-phase liquid chromatography (RPLC) among most important tests (bio)pharmaceutical industry release stability indicating measurements including content, identity, purity profile. However, time constraints developing “on-demand” robust methods prior each change can easily lead sample analysis becoming bottleneck development. Herein simple efficient generic framework capable chromatographically resolving commonly used non-aluminum based across academic industrial sectors introduced. This was designed seek more proactive approach assay endeavors evolved extensive stationary phase screening conjunction with multifactorial silico simulations retention (RT) as function gradient time, temperature, organic modifier blending, buffer concentration. models yield 3D resolution maps excellent baseline all single run, which found be very accurate, differences between experimental simulated times less than 1%. described here also includes introduction versatile by introducing dynamic RT database covering entire library broad mechanisms action numerous formulations linearity, accuracy, precision, specificity. power this demonstrated generated rapidly guiding processes formulations. Analytical work covers profile RPLC-UV-CAD, component identification (RPLC-MS) formulations, surfactants (e.g., polysorbates), well targets.

Language: Английский

Citations

1
Digitally Enabled Generic Analytical Framework Accelerating the Pace of Liquid Chromatography Method Development for Vaccine Adjuvant Formulations DOI
Mohamed Hemida, Rodell C. Barrientos,

Caleb Kinsey

et al.

ACS Pharmacology & Translational Science, Journal Year: 2024, Volume and Issue: 7(10), P. 3108 - 3118

Published: Sept. 11, 2024

The growing use of adjuvants in the fast-paced formulation new vaccines has created an unprecedented need for meaningful analytical assays that deliver reliable quantitative data from complex adjuvant and adjuvant-antigen mixtures. Due to their chemical physical properties, method development separation vaccine is considered a highly challenging laborious task. Reversed-phase liquid chromatography (RPLC) among most important tests (bio)pharmaceutical industry release stability indicating measurements including content, identity, purity profile. However, time constraints developing "on-demand" robust methods prior each change can easily lead sample analysis becoming bottleneck development. Herein, simple efficient generic framework capable chromatographically resolving commonly used non-aluminum-based across academic industrial sectors introduced. This was designed seek more proactive approach assay endeavors evolved extensive stationary phase screening conjunction with multifactorial

Language: Английский

Citations

1