Capitalizing on key NIH investments in technologies for the development of novel therapeutics [ 21, 47, 49], the workgroup reports puts in place a smooth and efficient process for intervention discovery, from pre-clinical studies to Phase I safety and dose finding studies in typical humans through proof-of-concept Phase II studies, and the establishment of clinical efficacy.
To develop such biomarkers, integrated animal human studies are needed with an important role for systems biology to understand better the molecular basis of the critical pro-aging processes targeted for intervention and the mechanistic rationale of potential interventions.
However, it is thought that the process for interventions, particularly regarding activity-based approaches such as CST, is not necessarily the same as that for assessments.
It is also vital that the planning process for interventions in post areas is based on accurate data to improve program effectiveness.
Considerable advances have recently been made in the generation of small-molecule inhibitors of chromatin regulators, raising the possibility of targeting chromatin processes for therapeutic intervention.
It also discusses the implications of dual-process models for intervention research.
We aimed to address this gap in the current evidence-base through the development of a systematic intervention modelling process (IMP) for intervention development and evaluation that corresponds to each of the theoretical, modelling and experimental phases of the MRC Framework [ 14].
Determining whether the current context is similar to the context examined in a mortality study requires corroborating evidence, which leads us to our next question to determine if findings can and should be applied to the decision-making process required for intervention.
The need for in-country guidance on the set-up costs and technical assistance on budgeting and planning processes for specific interventions for small and sick babies, such as KMC and special care units, was specifically highlighted.
The backend system would take the user input and continue offline processing, queuing up any additional frames that are difficult to process for human intervention.
