Adaptive Optimal Control of Continuous Aqueous Two-Phase Flotation (ATPF)

活性成分，如mRNA疫苗，被封装在脂质体或液体纳米颗粒中。因此，磷脂在活性成分周围形成一层外壳，保证其进入人体。通过酶对两亲性磷脂的特定修饰，例如从疏水尾部切割脂肪酸，使人们能够稳定不同的活性成分。有各种各样的磷脂酶，每一种都能在不同的位点水解磷脂，从而特异性地改变它们的性质以提高质量。磷脂酶是一种技术酶，在许多工业应用中作为生物催化剂起着至关重要的作用。它们的独特性质不仅用于制剂，而且用于化妆品和食品生产。这导致了对磷脂酶的大量需求，这只能通过微生物发酵和高效的下游处理来满足，从发酵液中回收酶。因此，该项目的目的是将连续水相浮选（ATPF）转化为磷脂酶回收和纯化的自动控制过程，可以很容易地从复杂的生物悬浮液中转移到其他生物技术产品。实验重点由卡尔斯鲁厄理工学院机械过程工程研究所（Hermann Nirschl教授）负责，包括建立合适的在线测量方法来确定磷脂酶的浓度和活性。与弗莱堡大学微系统工程研究所（Moritz Diehl教授）密切合作，创建了连续ATPF过程的新系统模型。该系统模型实现了Freiburg开发的两阶段非线性模型预测控制（NMPC），并结合了能够在线学习零阶和一阶模型修正的估计方法，以确保在各种过程条件下的最优稳态运行。在第一个资助期结束时，一个能够适应ATPF模型并对基于在线测量的干扰作出反应的闭环控制系统将在实验室规模上可用。在第二个资助期，通过超离心将磷脂酶从浓缩酶溶液中进一步分离将整合到受控工艺链中。

Active ingredients, like mRNA vaccines, are encapsulated within liposomes or liquid nanoparticles. Thereby, phospholipids form an outer shell around the active ingredient and ensure the transport into the human body. Specific modifications of the amphiphilic phospholipids by enzymes, for example the cleavage of fatty acid from the hydrophobic tail allow one to stabilize different active ingredients. There are various phospholipases, each of which hydrolyzes phospholipids at different sites and thus specifically alters their properties for an improved quality. Phospholipases are technical enzymes that play a crucial role as biocatalysts in many industrial applications. Their unique properties are used not only in the formulation of pharmaceutics but also in cosmetics and food production. This leads to a large demand for phospholipases, which can only be met by microbial fermentation and efficient downstream processing to recover the enzymes from the fermentation broth.The aim of this project is therefore to convert continuous aqueous two-phase flotation (ATPF) into an automatically controlled process for phospholipase recovery and purification that can be easily transferred to other biotechnological products from complex biosuspensions. The experimental focus is being handled by the Institute of Mechanical Process Engineering at the Karlsruhe Institute of Technology (Prof. Hermann Nirschl), including the establishment of suitable online measurement methods to determine the concentration and activity of the phospholipases. In close cooperation with the Institute of Microsystems Engineering of the University of Freiburg (Prof. Moritz Diehl) a new system model of the continuous ATPF process is created. The system model enables two-stage nonlinear model predictive control (NMPC), which is developed in Freiburg and combined with an estimation method capable of learning zero- and first-order model corrections online to ensure optimal steady-state operation under various process conditions.At the end of the first funding period, a closed-loop control system, that is able to adapt the ATPF model and to react to disturbances based on online measurements, shall be available on a laboratory scale. In the second funding period, the further separation of phospholipases from the concentrated enzyme solution by ultracentrifugation will be integrated into the controlled process chain.