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Updated: Jan 10, 2026
Characterization of Sickling During Controlled Automated Deoxygenation with Oxygen Gradient Ektacytometry
Published on: November 5, 2019
In Silico Post-screening of Anti-polymerization Agents to Treat Sickle Cell Disease
Ying Qian1, Nazanin Ahmadi Daryakenari2, Melissa Hallow1
1School of Chemical, Materials, and Biomedical Engineering, University of Georgia, Athens, GA 30602.
Insights
A new computational platform predicts sickle cell disease drug efficacy by combining pharmacokinetic models with red blood cell sickling kinetics. This tool aids in developing better anti-sickling agents and optimizing treatment strategies for patients.
Area of Science:
- Computational biology and bioinformatics
- Pharmacology and drug discovery
- Hematology and genetic blood disorders
Background:
- Sickle cell disease (SCD) affects millions globally, with limited treatment options beyond costly curative therapies.
- Current FDA-approved drugs for SCD do not fully address all disease symptoms or crises.
- Existing in vitro drug screening assays for SCD lack physiological relevance, failing to account for organ-specific oxygen levels and drug pharmacokinetics (PK)/pharmacodynamics (PD).
Purpose of the Study:
- To develop and validate a computational platform for post-screening analysis of potential anti-sickling agents.
- To integrate PK/PD models with RBC sickling kinetics for predicting drug efficacy under patient-specific conditions.
- To evaluate the therapeutic potential of existing and novel anti-SCD agents and assess the impact of drug noncompliance.
Main Methods:
- Development of a computational platform combining PK/PD models with a kinetic model of red blood cell (RBC) sickling.
- Sequential analysis to predict dosage-dependent therapeutic efficacy based on patient hematological factors and organ-specific oxygen levels.
- Validation using FDA-approved drugs (Hydroxyurea, voxelotor) and clinical trial agents (Bitopertin, osivelotor), including multi-agent therapies and noncompliance scenarios.
Main Results:
- The platform successfully predicted the efficacy of Hydroxyurea and voxelotor.
- Osivelotor demonstrated comparable anti-sickling effects to voxelotor at significantly lower doses due to improved PK properties.
- Bitopertin showed less pronounced anti-sickling effects compared to established treatments; the platform also quantified noncompliance risks for voxelotor and osivelotor.
Conclusions:
- The developed in silico platform is a valuable tool for assessing anti-sickling agents' PK and efficacy before clinical trials.
- The platform provides insights into patient-specific treatment responses and the consequences of drug noncompliance.
- Findings guide optimization of drug dosage strategies to mitigate risks associated with noncompliance in sickle cell disease management.
Abstract:
Sickle cell disease (SCD) is a genetic disorder that affects approximately 100,000 individuals in the United States and millions globally. Although curative therapies, such as stem cell transplant and gene therapy, are available, their application is limited by high cost and donor availability. Consequently, drug therapy remains the most feasible treatment option for the majority of patients with SCD. To date, only four drugs have been approved by the FDA, but none of these treatments comprehensively address all SCD-related symptoms or crises, suggesting the pressing need for developing new drugs. Several high-throughput screening campaigns have been performed for SCD drug discovery based on the in vitro sickling of red blood cells (RBCs) and they have identified several hits. However, it is challenging to replicate the organ-specific oxygen level and physiological deoxygenation time in these in vitro RBC sickling assays. Furthermore, these assays do not consider the pharmacokinetics (PK) and pharmacodynamics (PD) of the identified drugs, which are essential to determine whether the drugs can provide robust and sustained efficacy in treated patients with SCD. To address these technical gaps, we have developed a computational platform to perform post-screening analysis of potential anti-sickling agents. This platform sequentially combines PK/PD models with a kinetic model of RBC sickling, enabling efficient prediction of the dosage-dependent therapeutic efficacy of various anti-sickling agents based on patient-specific hematological factors and organ-specific oxygen levels. We first demonstrate the effectiveness of our integrated platform by showcasing the therapeutic efficacy of two FDA-approved drugs, Hydroxyurea (HU) and voxelotor. Next, we evaluate the therapeutic efficacy of two potential anti-sickling agents under clinical trial, namely Bitopertin and osivelotor. Our findings suggest that Bitopertin exhibits anti-sickling effects that are considerably less pronounced than those of HU and voxelotor. On the other hand, osivelotor can achieve similar anti-sickling effects as voxelotor with significantly lower doses due to its improved PK properties. Furthermore, we show the versatility of the proposed platform in predicting the anti-sickling effect of multi-agent therapies and evaluate the consequences of drug noncompliance. In particular, our analysis indicates that noncompliance with voxelotor may result in rapid increases in RBC sickling, whereas osivelotor is likely to mitigate noncompliance-induced adverse effects due to improved PK properties. We further quantify the relationship between drug dosage and the duration of noncompliance that leads to loss of therapeutic efficacy for voxelotor and osivelotor, providing guidance for optimizing dosage strategies to reduce the risk associated with noncompliance. In summary, our in silico platform serves as a valuable tool for post-screening analysis of potential anti-sickling agents by considering their PK and anti-sickling efficacy under patient-specific hemoglobin level and organ-specific oxygen level, thereby gaining insights into their potential therapeutic efficacy alone or in combination before clinical trials.
