Decisional tools for end-to-end value chain analysis of cell and gene therapies

该项目将专注于罗氏感兴趣的整个细胞和基因治疗(CGT)组合的预测成本建模(如自体和异体基因修饰细胞疗法、体细胞干细胞疗法、体内基因疗法、个性化RNA癌症疫苗)。该项目的重点是根据端到端(E2E)价值链和产品生命周期开发各种不同的成本模型，并最终将不同的成本模型结合到一个商业可行性评估框架中。目标是为CGTS创建一个先进的E2E成本建模决策工具，该工具包括以下元素：当前和新兴细胞和基因疗法的详细商品成本CGT模型。这将为每个产品和流程的每个阶段确定更具成本效益的技术和纵向扩展/横向扩展解决方案。CGT项目生命周期模型将捕捉实施制造更改以实现成本降低时的权衡，以及对CGT生命周期成本的影响，其中包括开发成本(过程开发、化验开发、技术转让、可比性、验证、现场许可)，不同模式的临床流失率和上市速度。探索集中式和分散式制造场景的商业供应链模型。风险分析工具，以确定解决方案的稳健性，以应对流程和来源的多样性。E2E投资组合成本建模工具，集成上述模型并将它们链接到优化算法，以确定不同场景的最佳投资组合构成。将设计一组与行业相关的案例研究，以说明模型的能力，并提供对每种模式价值链的特殊性的洞察，以实现战略决策。

This project will focus on predictive cost modelling across the whole cell and gene therapy (CGT) portfolio of interest to Roche (such as autologous and allogeneic gene-modified cell therapies, somatic stem cell therapies, in vivo gene therapies, personalised RNA cancer vaccines). The focus of this project is the development of various different cost models in accordance with the end-to-end (E2E) Value Chains and product lifecycle and ultimately the combination of the different cost models to a business feasibility assessment framework.The goal will be to create an advanced E2E cost modelling decisional tool for CGTs that comprises the following elements:Detailed CGT cost of goods models for current and emerging cell and gene therapies. This will enable identification of more cost-effective technologies and scale-up/out solutions for each product and each stage of the process.CGT Project lifecycle models that will capture the trade-offs when implementing manufacturing changes to achieve cost reduction and the consequences on CGT lifecycle costs that include the cost of development (process development, assay development, tech transfer, comparability, validation, site licence), clinical attrition rates and speed to market for the different modalities.Commercial supply chain models that explore centralised versus decentralised manufacturing scenarios.Risk analysis tools to determine the robustness of solutions to cope with process and source variability.E2E Portfolio cost modelling tool that integrates the above models and links them to an optimisation algorithm to identify the optimal portfolio composition for different scenarios.A set of industrially relevant case studies will be devised to illustrate the capabilities of the models and to provide insights into the specificities of each modality's value chain that enable strategic decision- making.