(T1130-03-15) Development of a 96-Well Microplate Reader-Based Method for High-Throughput Screening of Antiplatelet Effects in Rat Platelet-Rich Plasma for Drugs and Herbal Components

Purpose: Activated and aggregated platelets are the primary contributors to ischemic stroke ^{[1, 2]}.Antiplatelet drugs, such as aspirin and clopidogrel, inhibit platelet aggregation and serve as an effective standard therapy recommended in clinical stroke guidelines ^{[3, 4]}. For platelet aggregation testing, light transmission aggregometry (LTA) is widely acknowledged as the gold standard method, but it requires a large volume (200-300 μL) of platelet-rich plasma (PRP) for each single test using aggregometer. Although a 96-well microplate reader-based LTA method has been established, its application is currently limited to human PRP or washed platelets ^[5-7]. There remains a need for a method suitable for preclinical high-throughput screening of the antiplatelet effects of potential compounds while minimizing the volume of PRP required. Agonists of platelet aggregation, including adenosine diphosphate (ADP), arachidonic acid (AA) and platelet-activating factor (PAF), represent three different pathways involved in the process of platelet aggregation. The current study aims to develop a 96-well based method for high-throughput screening of inhibitory effects of drugs and herbal components on platelet aggregation induced by ADP, AA and PAF.

Methods: The 96-well based platelet aggregation testing method was developed using a microplate reader equipped with kinetic, shaking and 37 ℃ incubation modes. Following the optimization of rat PRP preparation method, PRP platelet counts and shaking parameters (method, speed, and duration), we employed agonists of platelet aggregation ADP, AA and PAF to determine their EC₅₀ and concentrations for subsequent screening. The testing compounds include antiplatelet drugs aspirin (ASA), clopidogrel (CLP) and their metabolites—salicylic acid (SA), clopidogrel inactive metabolite (CLPM), and clopidogrel active metabolite derivative (CAMD). Additionally, herbal components 3-n-butylphthalide (NBP), ginkgolide A (GA), ginkgolide B (GB) and ginkgolide K (GK) from two most used herbal preparations for ischemic stroke treatment ^[8] were evaluated. To evaluate their inhibitory effects, 10 μL of tested compounds at serial concentrations/0.5% DMSO as vehicle control were added into 90 μL rat PRP (2.5 × 10⁸/mL platelets) in a 96-well microplate followed by incubation at 37℃ for 30 minutes to measure the absorbance at 650 nm as an initial record (OD_inital). Subsequently, 10 μL of agonist at optimized concentrations were added to initiate the kinetic reading process, which consisted of 20 cycles with 30 seconds per cycle and a total duration of 600 seconds. Each cycle involved measuring absorbance at 650 nm for 15 seconds (OD_induced), followed by orbital shaking at 700 rpm for 12 seconds and standstill for 3 seconds. PPP absorbance served as the reference for 100% aggregation (OD_100%). The Aggregation Rate of each sample at each time point was calculated using the equation: Aggregation Rate(%)=[(OD_initial−OD_induced)/(OD_initial−OD_100%)]×100%. The Maximal Aggregation Rate (MAR) of both vehicle control (MAR_control) and tested drug/herbal components samples (MAR_testing) were obtained to calculate the Inhibition Rate (%) of each compound for evaluations and comparisons of their antiplatelet effects as equation: Inhibition Rate(%)=[(MAR_control−MAR_testing)/MAR_control)]×100%.

Results: The optimized preparation methods for rat PRP and platelet-poor plasma (PPP) were shown in Figure 1. Based on the absorbance at 650 nm of PRP and PRP/PPP ratio with varying platelet counts exhibited linear correlations (Figure 2), PRP with platelet counts of 2.5 × 10⁸/mL was selected for the subsequent tests. In addition, the optimal shaking parameters were determined to be orbital mode with 700 rpm speed for 12 seconds. As shown in Figure 3, dose-dependent responses (Figure 3 (i)) were observed for ADP, AA, and PAF, with EC₅₀ values (Figure 3 (ii)) of 4.67 μM, 0.27 mM, and 1.64 μg/mL, respectively. Therefore, the optimal agonist concentrations were determined to be 5 μM for ADP, 0.5 mM for AA, and 5 μg/mL for PAF. Results of the subsequent screening of selected compounds at various concentration ranges were summarized in Table 1. It was noted that antiplatelet drug ASA exhibited potent inhibitory effects on platelet aggregation induced by ADP and AA, whereas CLP (used as prodrug) did not exhibit any inhibitory effects. Among the tested herbal components, NBP demonstrated certain degree of inhibition on ADP-, AA- and PAF-induced platelet aggregation, but only at concentrations above 100 μM. Although GA, GB and GK also exhibited inhibitory effects on platelet aggregation induced by ADP and AA at concentrations over 50 μM, they demonstrated stronger inhibitory effects on PAF-induced platelet aggregation at much lower concentrations (10 μM for GA, 0.1 μM for GB and GK). Despite similar chemical structures, GA, GB and GK exhibited different inhibitory effects on ADP-, AA- and PAF-induced platelet aggregation, with effective concentrations in order of GK (10 μM)< GA~GB (100 μM), GK~GA~GB (50 μM), and GK~GB (0.1 μM)< GA (10 μM), respectively.

Conclusion: We for the first time developed a 96-well microplate reader-based platelet aggregation assay for high-throughput screening of components with antiplatelet effects. Among the tested compounds, ASA, NBP, GA, GB and GK demonstrated inhibitory effects on platelet aggregation via ADP-, AA- and PAF-induced pathways.

References: [1] Shaik, N. F., Regan, R. F., & Naik, U. P. (2021). Platelets as drivers of ischemia/reperfusion injury after stroke. Blood advances, 5(5), 1576–1584.
[2] Sikora, J., Karczmarska-Wódzka, A., Bugieda, J., & Sobczak, P. (2022). The Importance of Platelets Response during Antiplatelet Treatment after Ischemic Stroke-Between Benefit and Risk: A Systematic Review. International journal of molecular sciences, 23(3), 1043.
[3] Mendelson, S., & Prabhakaran, S. (2021). Diagnosis and Management of Transient Ischemic Attack and Acute Ischemic Stroke: A Review. JAMA, 325(11), 1088-98.
[4] Kleindorfer, D. O., Towfighi, A., Chaturvedi, S., Cockroft, K. M., Gutierrez, J., Lombardi-Hill, D., Kamel, H., Kernan, W. N., Kittner, S. J., Leira, E. C., Lennon, O., Meschia, J. F., Nguyen, T. N., Pollak, P. M., Santangeli, P., Sharrief, A. Z., Smith, S. C., Jr, Turan, T. N., & Williams, L. S. (2021). 2021 Guideline for the Prevention of Stroke in Patients With Stroke and Transient Ischemic Attack: A Guideline From the American Heart Association/American Stroke Association. Stroke, 52(7), e364–e467.
[5] Walkowiak, B., Kesy, A., & Michalec, L. (1997). Microplate reader--a convenient tool in studies of blood coagulation. Thrombosis research, 87(1), 95–103.
[6] Lordkipanidzé, M., Lowe, G. C., Kirkby, N. S., Chan, M. V., Lundberg, M. H., Morgan, N. V., Bem, D., Nisar, S. P., Leo, V. C., Jones, M. L., Mundell, S. J., Daly, M. E., Mumford, A. D., Warner, T. D., Watson, S. P., & UK Genotyping and Phenotyping of Platelets Study Group (2014). Characterization of multiple platelet activation pathways in patients with bleeding as a high-throughput screening option: use of 96-well Optimul assay. Blood, 123(8), e11–e22.
[7] Hsu, H., Chan, M. V., Armstrong, P. C., Crescente, M., Donikian, D., Kondo, M., Brighton, T., Chen, V., Chen, Q., Connor, D., Joseph, J., Morel-Kopp, M. C., Stevenson, W. S., Ward, C., Warner, T. D., & Rabbolini, D. J. (2022). A pilot study assessing the implementation of 96-well plate-based aggregometry (Optimul) in Australia. Pathology, 54(6), 746–754.
[8] Ni, X., Lin, H., Li, H., Liao, W., Luo, X., Wu, D., Chen, Y., Cai, Y., & Evidence-based Practice Guideline on Integrative Medicine for Stroke working team, Neurology Chapter of China Association of Chinese Medicine, Neurology Committee of Guangdong Provincial Association of Chinese Medicine, and Stroke Committee of Guangdong Provincial Association of Chinese Integrative Medicine (2020). Evidence-based practice guideline on integrative medicine for stroke 2019. Journal of evidence-based medicine, 13(2), 137–152.

Acknowledgements: Funding support from Guangdong-Hong Kong-Macao Joint Laboratory for New Drug Screening


Figure 1. Optimized procedures for rat PRP and PPP preparation


Figure 2. Correlations between PRP absorbance at 650 nm with platelet counts (Left) and the ratio of PRP/PPP with platelet counts (Right)
Figure 3. Platelet aggregation response versus time profiles (i) of (A) ADP 0.1-10 μM, (B) AA 0.1-0.75 mM and (C) PAF 0.1-10 μg/mL and their corresponding EC50 determination (ii).


Table 1. Summary of antiplatelet effects of commonly used drugs and herbal components