EMD Serono, Merck KGaA, Billerica, MA, USA.
EMD Serono, Merck KGaA, Billerica, MA, USA.
Prog Biophys Mol Biol. 2018 Nov;139:59-72. doi: 10.1016/j.pbiomolbio.2018.08.011. Epub 2018 Sep 7.
System based pharmacokinetic (PK) models can be used to study and predict the distribution of antibody based drugs into target tissues and assess the pharmacobinding (PB) of the drug to the target and the subsequent pharmacodynamic (PD) changes. In the absence of relevant PD readouts, compounded in cases of novel mechanisms, one can rely on binding between the drug and the target, computed as target occupancy (TO), as a relevant biomarker. This approach assumes that at maximum TO across the dosing interval, the drug-target interaction must demonstrate the intended pharmacology. Such analysis can help set laboratory objectives for protein engineers and chemists and guide them to the appropriate design and binding affinity of the molecule. Analysis of mechanistic models to guide affinity optimization against soluble and membrane-bound targets has been done for monoclonal antibodies (mAbs) (Tiwari et al., The AAPS Journal, 2017). However, comparable understanding of bispecific antibodies (BsAb; drugs with two targets, which are either soluble, membrane-bound, or a combination of the two) is still lacking. We propose to extend the work done by Tiwari et al. (2017) to BsAb. We focus on describing a generic BsAb with two membrane-bound targets, and explore the impact of various parameters on the TO of the BsAb to each target. Performed analysis can guide the optimization of dissociation constant (K) of the BsAb, and can also help in identifying druggable targets. Proposed model can be modified and tailored to specific biologics as needed.
基于系统的药代动力学 (PK) 模型可用于研究和预测抗体类药物在靶组织中的分布，评估药物与靶标的结合（即药效学结合）以及随后的药效学（PD）变化。在缺乏相关 PD 结果的情况下，对于新颖机制的化合物，可依赖药物与靶标的结合作为相关生物标志物，其通过靶标占有率（TO）来计算。该方法假设在整个给药间隔内达到最大 TO，药物-靶标相互作用必须表现出预期的药理学。这种分析可以帮助确定蛋白工程师和化学家的实验室目标，并指导他们设计和确定分子的结合亲和力。针对单克隆抗体（mAbs）（Tiwari 等人，《美国药学会杂志》，2017）已经进行了针对可溶性和膜结合靶标进行机制模型分析以指导亲和力优化的研究。然而，对于双特异性抗体（BsAb；具有两个靶标的药物，这两个靶标可以是可溶性的、膜结合的或两者的组合），仍然缺乏类似的理解。我们建议将 Tiwari 等人（2017）的工作扩展到 BsAb。我们专注于描述具有两个膜结合靶标的通用 BsAb，并探讨各种参数对 BsAb 对每个靶标的 TO 的影响。所进行的分析可以指导 BsAb 的解离常数（K）的优化，并且还可以帮助确定可成药的靶标。根据需要，所提出的模型可以进行修改和定制，以适应特定的生物制剂。
