A multi-material 3D printing offers nearly endless possibilities for the spatial arrangement of individual materials within the object being printed. In the case of pharmaceutical tablets, the spatial arrangement of individual material domains containing the active pharmaceutical ingredients (APIs) and excipients uniquely defines the release profiles of the APIs. However, the inverse is not necessarily true – identical or very similar dissolution profiles can potentially be obtained from different tablet internal structures, implemented as a combination of domains containing excipients with different individual dissolution rates and different local API concentration. This work presents a computational method based on an Evolutionary Algorithm for the solution of the inverse problem, i.e. finding such tablet internal structure that results in a prescribed dissolution profile of each API contained in the tablet. After testing the algorithm on cases with a known solution, the methodology is applied to a problem of finding tablet structures that result in delayed release and step-wise release profiles, respectively. When combined with patient-specific requirements on drug release profiles, the algorithm can serve as a tool for an automated design of 3D-printed tablets in the framework of personalised medicine.

多材料 3D 打印为打印对象内单个材料的空间排列提供了几乎无限的可能性。对于药片，包含活性药物成分 (API) 和赋形剂的各个材料域的空间排列独特地定义了 API 的释放曲线。然而，反过来不一定正确——相同或非常相似的溶出曲线可能从不同的片剂内部结构中获得，实现为包含具有不同个体溶出速率和不同局部 API 浓度的赋形剂的域的组合。这项工作提出了一种基于进化算法的计算方法来解决逆问题，即 找到这样的片剂内部结构，导致片剂中包含的每种 API 的规定溶出度曲线。在具有已知解决方案的情况下测试算法后，该方法被应用于寻找分别导致延迟释放和逐步释放曲线的片剂结构的问题。当结合患者对药物释放曲线的特定要求时，该算法可以作为在个性化医疗框架内自动设计 3D 打印药片的工具。