Droplet based microfluidics
The word pharmacogenomics combines the field of pharmacology that emphasizes on study of usage and effect of medications along with genomics or study of gene functions. It is the study of how an individual’s genetic variants influence drug responses, including the variants associated with adverse drug reaction (ADR) and treatment efficacy. The variable drug responses are due to polymorphisms of genes encoding the enzymes, transporters and receptors underlying the pharmacokinetic and pharmacodynamics pathways.1
More broadly, medical practice is moving away from the concept of “one size fits all” medications, as drugs that help some patients will not work for others, and the same drug may have adverse effects in some patients (Figure 1).2
Pharmacogenomics deals with the influence of genetic variation on drug response in patients by correlating gene expression or single nucleotide polymorphism (SNPs) with a drug’s efficacy or toxicity. By doing so, pharmacogenomics aims to develop rational means to optimize drug therapy, with respect to the patients’ genotype, to ensure maximum efficacy with minimal adverse reactions. Such approaches promise the advent of ‘personalized medicine’, in which drugs and drug combinations are optimized for each individual’s unique genetic makeup.3 In the pursuit of understanding pharmacogenomics, it is essential to explore the landscape of single nucleotide polymorphisms (SNPs). These genetic variations play a pivotal role in shaping individual responses to medications and hold immense potential in tailoring treatment strategies for personalized medicine.
In pharmacogenomics, genomic information is used to study individual responses to drugs. When a gene variant is associated with a particular drug response in a patient, there is the potential for making clinical decisions based on genetics by adjusting the dosage or choosing a different drug, for example. Scientists assess gene variants affecting an individual’s drug response the same way they assess gene variants associated with diseases: by identifying genetic loci associated with known drug responses, and then testing individuals whose response is unknown. Modern approaches include multigene analysis or whole-genome single nucleotide polymorphism (SNP) profiles, and these approaches are just coming into clinical use for drug discovery and development.4
When studying drug action in individuals, researchers focus on two major determinants: (1) how much of a drug is needed to reach its target in the body, and (2) how well the target cells, such as heart tissue or neurons, respond to the drug. The scientific terms for these two determinants are pharmacokinetics and pharmacodynamics, and both are critical considerations in the field of pharmacogenomics (Figure 2).4
Pharmacogenomics is increasingly incorporated into clinical trials and drug development to utilize new significant genes and variants for predicting drug safety, efficacy, and toxicity, which can be applied in clinical practice. This field has the potential to impact outcomes related to drug dosing, effectiveness, and safety, leading to potential recommendations for clinical testing based on specific genes that inform medication selection and dosages. Pharmacogenomic research is instrumental in assessing the varying effects of chemical compounds in drug discovery and is commonly used to guide decisions on gene expression modulation in experimental setups. The primary objective of pharmacogenomics studies is to ensure healthcare providers apply precision medicine findings, aiming to customize treatments according to an individual’s genetic makeup, lifestyle, environmental influences, and other factors as part of a significant healthcare initiative.6
Microfluidics lab-on-a-chip technology has significantly impacted the field of biomedical research by enabling the miniaturization, integration, and automation of (bio-)chemical assays.⁸ This technology allows for precise analysis of biological samples at the single-cell level within a compact device, offering a substantial advancement over conventional methods.⁹ By utilizing microfluidic platforms, researchers can conduct a wide range of experiments, from cell culture studies to organ-on-a-chip models, with enhanced physiological relevance.¹⁰ The concept of lab-on-chip aims to integrate various laboratory functions onto a small chip, facilitating automated microfluidics and high-throughput screening.¹¹
Organ-on-a-chip (OoC) technology has gained prominence in drug development and clinical drug testing due to its ability to mimic the genetic characteristics of individual patients’ cells (Figure 4). OoC involves creating controlled compartments that replicate the cellular behavior of target tissues, allowing for the study and manipulation of cell responses to different drug stimuli. This technology has advanced through the integration of microfluidic systems, engineered biomimetic tissues, and non-invasive monitoring systems, addressing the limitations of traditional drug testing models. Human-induced pluripotent stem cells (hiPSCs) play a crucial role in OoC, as they can be derived from a patient’s skin tissue or directly from pathogenic cells, enabling the development of personalized tissue constructs or disease models. The hiPSCs’ ability to differentiate into various cell types and generate diverse tissues or organoids makes OoC a valuable tool for studying complex drug interactions across multiple organ systems.¹²
Kornaros and colleagues conducted a study on a consumer lab-on-chip designed for pharmacogenomics, offering valuable insights into a portable device’s architecture and functionality for customizing drug treatments. This lab-on-chip system, tailored for consumer use, allows individuals to conveniently access information about their genetic characteristics and how these may influence their response to specific medications. The system uses a disposable device-cartridge which first extracts the DNA from a blood drop, then it amplifies the fragmented tiny DNA samples (using PCR). Through the integration of microfluidics, bioinformatics, and miniaturized analytical tools, this technology enables swift and precise genotyping in a compact and user-friendly format. One key implication of this research is the potential for personalized medicine to become more accessible to the general public, as the consumer lab-on-chip device provides a convenient and cost-effective solution for individuals to obtain personalized pharmacogenomic information without requiring specialized laboratory equipment or expertise. The integrated microsystem is well-suited for a compact consumer device optimized to identify the appropriate cluster of a pharmacogenomic drug for a patient in under 30 minutes.¹³
In a separate study, Zhu and colleagues introduce a novel method for genotyping utilizing microfluidic technology (Figure 5). The research centers on the creation of a microfluidic device capable of concurrently analyzing multiple single-nucleotide polymorphisms (SNPs) in a high-throughput manner. SNPs, which are variations in a single nucleotide occurring at specific positions in the genome, are extensively studied for their links to various diseases and traits.
The microfluidic device outlined in the study presents several advantages over conventional genotyping methods. The key steps involved in SNP microfluidic genotyping include sample preparation of C18 silica microspheres and streptavidin beads, which are rinsed to create optimal binding conditions. Then, the sample with target template and SBE reagent is introduced into the SBE chamber and goes through 30 thermal cycles that involve incubation at 94°C for 15 seconds, followed by 40°C for 60 seconds, and finally 69°C for 30 seconds. This thermal cycling facilitates the specific extension of the primer at the SNP site. Next the SBE product is put into the SPP chamber and extracted under continuous flow conditions. The primer extension product is released from streptavidin beads then characterized using a MALDI-TOF (matrix assisted laser desorption ionization-time of flight) mass spectrometer. These steps collectively enable the accurate and efficient identification of single nucleotide polymorphisms in the target DNA sequence. Through the utilization of microfluidic technology, the device allows precise control over sample handling and manipulation at the microscale level, facilitating efficient and accurate analysis of multiple SNPs in a single experiment, thereby reducing the time and resources needed for genotyping. A key feature of the microfluidic device is its capacity for multiplex genotyping, enabling the simultaneous analysis of multiple SNPs. This capability is particularly beneficial in large-scale genetic studies, where analyzing multiple SNPs concurrently can offer a more comprehensive understanding of genetic variations and their implications.14
Organ-on-a-chip (OoC) technology has emerged as a valuable tool in pharmacogenomics, offering a platform to study the genetic characteristics of individual patients’ cells in drug development and clinical testing models.
The field of pharmacogenomics is growing, and new approaches are under study in clinical trials. In the future, pharmacogenomics will be used to develop tailored drugs to treat a wide range of health problems, including cardiovascular disease, Alzheimer’s disease, cancer, and asthma.15
Chowdhury et. al presented a study on the investigation on the microfluidic platform for genotyping single nucleotide polymorphisms (SNPs) of the thiopurine S-methyltransferase (TPMT) gene to evaluate the risk of adverse drug events yielded significant insights. The TPMT enzyme plays a significant role in metabolizing thiopurine drugs, commonly used in leukemia treatment. Variations in individual enzyme activity stem from genetic polymorphisms in the TPMT gene found on chromosome 6. Approximately 14% of the population exhibits reduced enzyme activity. When these individuals are administered standard doses of thiopurines, they face an elevated risk of severe Adverse Drug Reactions (ADR) such as myelosuppression or gastrointestinal intolerance.
In this study, the adoption of a microfluidic platform facilitated efficient and high-throughput genotyping of TPMT gene variants, enabling swift analysis of SNPs in the TPMT gene critical for predicting an individual’s response to thiopurine medications. Also, the research showcased the clinical significance of TPMT genotyping in assessing the risk of adverse drug events linked to thiopurine therapy. By identifying specific TPMT gene variants in patients, healthcare providers can tailor drug dosages to reduce the chances of severe side effects. This personalized medicine approach based on TPMT genotyping has the potential to enhance treatment outcomes and patient safety. In summary, the study emphasized the importance of preemptive TPMT genotyping before commencing thiopurine therapy and how microfluidic platform for TPMT genotyping provided valuable insights into the role of genetic testing in predicting adverse drug events related to thiopurine medications. 16
Currently most cancer patients are not treated in a personalized way, but biomarkers with known correlation to drug effect are analyzed where possible. To avoid resistances, therapies based on drug combinations are beneficial. Novel approaches will enable the most efficient combinations to be determined using a combination of biomarker and phenotypic data (Figure 6). Patients should then be monitored during treatment and even after, to track disease status and adapt treatment if necessary.17
Precision oncology challenges the conventional approach of uniform treatment strategies by focusing on individualized care based on molecular tumor characteristics. Patients undergo screening for specific genetic alterations to predict treatment responses, aiming for personalized and effective therapies. In this context, functional assays assessing treatment efficacy directly on patient cells provide a valuable complement to molecular profiling. However, traditional Petri dish-based assays may not capture the full complexity of tumors, thereby restricting their utility as predictive functional biomarkers.18
Microfluidics has emerged as a promising technology in the realm of cancer research and precision medicine. A study was conducted to explore the application of microfluidics in comprehending the intricate biology of malignant gliomas, aggressive brain tumors with a bleak prognosis. Through the utilization of microscale channels and chambers, researchers successfully replicated the tumor microenvironment, investigated cellular interactions, and assessed drug responses in a controlled environment.19
One key inference drawn from this study is the potential of microfluidic devices to offer personalized treatment approaches for individuals with malignant gliomas. By analyzing specific tumor characteristics and drug sensitivities using microfluidic platforms, healthcare providers can customize therapies to target precise molecular pathways and enhance treatment outcomes. This methodology aligns with the principles of precision medicine, which underscore the individualized tailoring of healthcare based on unique patient profiles.19
Moreover, the incorporation of microfluidics in malignant glioma research provides a platform for high-throughput screening of potential therapeutic agents. Through the downsizing of experimental assays and enhanced automation, researchers can efficiently evaluate drug candidates and pinpoint novel treatment possibilities for glioma patients. This streamlined drug discovery process has the potential to accelerate the translation of preclinical discoveries into clinical applications, ultimately benefiting individuals with malignant gliomas.19
In the study titled “Microfluidic-based dynamic BH3 profiling predicts anticancer treatment efficacy,” researchers investigated the use of microfluidic technology to predict the effectiveness of anticancer treatments. The study aimed to assess the potential of dynamic BH3 peptide profiling in determining the response of cancer cells to various treatment strategies.20
Dynamic BH3 profiling is a technique that evaluates the sensitivity of cancer cells to apoptosis induction by measuring the response of mitochondria to specific BH3 peptides. By utilizing microfluidic platforms, the researchers were able to create a controlled environment to study the interactions between BH3 peptides and cancer cells in real-time.20 The results of the study demonstrated that microfluidic-based (Figure 7) dynamic BH3 profiling could accurately predict the efficacy of anticancer treatments. By analyzing the mitochondrial response to BH3 peptides, researchers were able to identify which treatments would be most effective in inducing cell death in cancer cells20. Overall, the study highlights the potential of microfluidic-based dynamic BH3 profiling as a valuable tool in personalized cancer treatment. By providing a rapid and accurate assessment of treatment efficacy, this approach could help clinicians tailor treatment strategies to individual patients, ultimately improving outcomes in cancer therapy.20
Microfluidic platforms have been essential in the development of organ-on-a-chip (OoC) technology, which mimics the genetic characteristics of individual patients’ cells. By creating controlled compartments that replicate cellular behavior, OoC technology enables the study and manipulation of cell responses to different drug stimuli, offering a valuable tool for personalized medicine in pharmacogenomics.
The integration of microfluidics in pharmacogenomics research has led to the development of innovative approaches for genotyping SNPs, revolutionizing personalized medicine by offering faster, more cost-effective methods for analyzing genetic profiles. By enhancing the efficiency, accuracy, and throughput of genetic analysis, microfluidics technology contributes significantly to tailoring treatment strategies based on individual genetic makeup, ultimately improving patient outcomes in drug therapy.
You want to start using microfluidics for pharmacogenomic research? Check out our starter packs!
1. Sukri A, Salleh MZ, Masimirembwa C, Teh LK. A systematic review on the cost effectiveness of pharmacogenomics in developing countries: implementation challenges. The Pharmacogenomics Journal. 2022/05/01 2022;22(3):147-159. doi:10.1038/s41397-022-00272-w
2. Gill PS, Yu FB, Porter-Gill PA, et al. Implementing Pharmacogenomics Testing: Single Center Experience at Arkansas Children’s Hospital. Journal of Personalized Medicine. 2021;11(5). doi:10.3390/jpm11050394
3. Patrinos GP, Innocenti F. Conference Scene: Pharmacogenomics: paving the path to personalized medicine. Pharmacogenomics. 2010/02/01 2010;11(2):141-146. doi:10.2217/pgs.09.174
4. Cecchin E, Stocco G. Pharmacogenomics and Personalized Medicine. Genes (Basel). Jun 22 2020;11(6) doi:10.3390/genes11060679
5. Ahmed M. Pharmacogenetics: an Emerging Therapeutic option for Bangladesh. Dhaka University Journal of Pharmaceutical Sciences. 02/06 2015;13 doi:10.3329/dujps.v13i2.21902
6. Pharmacogenomics Overview and Goals. https://www.jliedu.com/blog/pharmacogenomics-overview-goals/
7. Organs on Chip Review. https://www.elveflow.com/microfluidic-reviews/organs-on-chip-3d-cell-culture/organs-chip-review/
8. Mark D, Haeberle S, Roth G, von Stetten F, Zengerle R. Microfluidic lab-on-a-chip platforms: requirements, characteristics and applications. 10.1039/B820557B. Chemical Society Reviews. 2010; 39(3):1153-1182. doi:10.1039/B820557B
9. Gupta K, Kim D-H, Ellison D, et al. Lab-on-a-chip devices as an emerging platform for stem cell biology. 10.1039/C004689B. Lab on a Chip. 2010;10(16):2019-2031. doi:10.1039/C004689B
10. Huh D, Matthews BD, Mammoto A, Montoya-Zavala M, Hsin HY, Ingber DE. Reconstituting organ-level lung functions on a chip. Science. Jun 25 2010;328(5986):1662-8. doi:10.1126/science.1188302
11. Neuži P, Giselbrecht S, Länge K, Huang TJ, Manz A. Revisiting lab-on-a-chip technology for drug discovery. Nat Rev Drug Discov. Aug 2012;11(8):620-32. doi:10.1038/nrd3799
12. Jodat YA, Kang MG, Kiaee K, et al. Human-Derived Organ-on-a-Chip for Personalized Drug Development. Curr Pharm Des. 2018;24(45):5471-5486. doi:10.2174/1381612825666190308150055
13. Kornaros G, Meidanis D, Papaeystathiou Y, Chantzandroulis S, Blionas S. Architecture of a Consumer Lab-on-Chip for Pharmacogenomics. 2008:1-2.
14. Zhu J. Genetic Analysis and Cell Manipulation on Microfluidic Surfaces. Columbia University; 2014. https://academiccommons.columbia.edu/doi/10.7916/D8SN0712
15. What is pharmacogenomics?
16. Chowdhury J, Kaigala GV, Pushpakom S, et al. Microfluidic platform for single nucleotide polymorphism genotyping of the thiopurine S-methyltransferase gene to evaluate risk for adverse drug events. J Mol Diagn. Sep 2007;9(4):521-9. doi:10.2353/jmoldx.2007.070014
17. Mathur L, Ballinger M, Utharala R, Merten CA. Microfluidics as an Enabling Technology for Personalized Cancer Therapy. Small. 2020/03/01 2020;16(9):1904321. doi:https://onlinelibrary.wiley.com/doi/10.1002/smll.201904321
18. Ayuso JM, Virumbrales-Muñoz M, Lang JM, Beebe DJ. A role for microfluidic systems in precision medicine. Nat Commun. Jun 2 2022;13(1):3086. doi:10.1038/s41467-022-30384-7
19. Logun M, Zhao W, Mao L, Karumbaiah L. Microfluidics in Malignant Glioma Research and Precision Medicine. Adv Biosyst. May 2018;2(5) doi:10.1002/adbi.201700221
20. Manzano-Muñoz A, Yeste J, Ortega MA, et al. Microfluidic-based dynamic BH3 profiling predicts anticancer treatment efficacy. NPJ Precis Oncol. Dec 1 2022;6(1):90. doi:10.1038/s41698-022-00333-0
21. Zhang L, Cai Q, Wiederkehr RS, et al. Multiplex SNP genotyping in whole blood using an integrated microfluidic lab-on-a-chip. 10.1039/C6LC01046F. Lab on a Chip. 2016;16(20):4012-4019. doi:10.1039/C6LC01046F
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