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Small Molecules: Process Intensification and Continuous Synthesis
Published in Anthony J. Hickey, Sandro R.P. da Rocha, Pharmaceutical Inhalation Aerosol Technology, 2019
Laboratory automation has improved the ability to quickly gather data for optimization of chemical reactions. One of the first generations of process automation was detailed by Emiabata-Smith et al. from GSK.18 This system, referred to as DART (development automated reaction toolkit), had integrated HPLC sampling which allowed the profiling of reactions over time. The DART had the ability to carry out ten reactions simultaneously which generated large amounts of reaction data. Prior to introduction of DART, collection of this amount of data would only been performed in order to solve a particularly intractable problem and not as a general process understanding tool which could be used on every reaction. Laboratory process development automation has made consistent progress since the introduction of the DART and recently been reviewed.19 As the capacity to carry out automated process development and gather reaction understanding progresses, other technologies such as weighing, sampling, and analytical testing must continue to evolve. In the case where parallel small scale reactions are planned, particularly in 96 well plates, solids weighing becomes a bottleneck. Two of the leading suppliers of automated reaction automation equipment, Chemspeed Technologies and Unchained Labs, (Freeslate system) both have developed weighing systems which can accurately dispense solids with accuracy less that 1 mg. These modern systems also have automated liquid handling systems and the ability to carry out reactions at a variety of conditions. Due to the nature of the integration, automation, and IT associated with these systems, their cost is beyond that of most academic institutions although most major pharmaceutical companies employ these systems regularly. The practical operation of the Freeslate and Chemspeed platforms also need to be considered, as it may not be practical to utilize these systems as walk-up platforms. In practice, a core group of trained lead-users may be a reasonable option for the operation of the units and should be used as an internal service group, working with chemists to plan and execute the complex experimental protocols.
Automated spectrophotometric platform for the quantification of multiple nucleic acid samples
Published in Instrumentation Science & Technology, 2021
Hoon Kang, Sang-Ryoul Park, Ju Hwang Kim, In-Yong Park, Hee-Bong Yoo, Inchul Yang, Haewon Jung
Because the demand for automatic analysis systems continues to grow, micro-volume spectrophotometers needed to be updated with laboratory automation. Thus, a prototype instrument platform equipped with a unique light absorption cell and a disk-type sample tray was developed and tested for the first time in the field of micro-volume spectrophotometry.[22] Although this prototype platform successfully demonstrated substantially enhanced absorption sensitivity, excellent repeatability, and automated operation, it still needed further improvement for commercial use. In this prototype platform, up to 18 samples could be accommodated on the disk-type sample tray and a single wavelength of light could be used for light absorbance measurement. In addition, a PC-based control system and software were used to control the components and to estimate light absorbance. These system configurations were suitable for laboratory tests or developmental stage, but not ideal for real-world applications.
Pathogen contamination of groundwater systems and health risks
Published in Critical Reviews in Environmental Science and Technology, 2023
Yiran Dong, Zhou Jiang, Yidan Hu, Yongguang Jiang, Lei Tong, Ying Yu, Jianmei Cheng, Yu He, Jianbo Shi, Yanxin Wang
Fast scientific and technological advances make it possible to overcome the technical hurdles in groundwater pathogen surveillance and analyses. For example, the widely applied paper-based test kits during COVID-19 pandemic are exemplary for pathogen detection in an easy and economical manner. Although in their infancy, emerging synthetic biology enables genetical modulation of cells with desired functionalities to construct pathogen-responsive biosensors (Cesewski & Johnson, 2020). Meanwhile, robotics and laboratory automation can improve scalability, safety and reproducibility over traditional surveillance strategies (Ko et al., 2022). Multi-omic techniques, including single-cell sequencing, will facilitate discovery and understandings of novel pathogens and their etiological mechanisms (Carr & Chaguza, 2021; Avital et al., 2022). When portable sequencing is coupled with appropriate apps, high-throughput genomic analyses will facilitate pathogen detection in areas with limited healthcare facilities and encourage broader participation of citizen scientists (Palatnick et al., 2020; Kovaka et al., 2021). In addition, the rapid development of information technologies such as artificial intelligence (AI) can translate big data to predict the effect of climate change on pathogen emergence (Lake & Barker, 2018). Groundwater biosafety-oriented dashboard and databases will provide real-time, reliable and accessible information about emerging outbreaks and the explosive growth of multi-omic data for the public, policymakers, scientists, and healthcare professionals worldwide. These multidisciplinary technologies will significantly enhance the efficacy of surveillance and fundamental studies on groundwater pathogens, which will be instructive for diagnosis and mitigation of the related contamination and diseases.
An automated approach for fibroblast cell confluency characterisation and sample handling using AIoT for bio-research and bio-manufacturing
Published in Cogent Engineering, 2023
Muaadh Shamhan, Ahmad Syahrin Idris, Siti Fauziah Toha, Muhammad Fauzi Daud, Izyan Mohd Idris, Hafizi Malik
In future research, the developed AIoT system for automated confluency estimation and sample handling could be improved by increasing the size and diversity of the dataset used for training the CNN model, exploring different CNN architectures or incorporating other segmentation techniques, and applying the system to other cell types or other laboratory automation tasks. Future research should also explore the potential societal implications of AIoT systems for laboratory automation, including their impact on the workforce, scientific research, and ethical considerations.