Timeline for Projects

Timeline for Projects2019-06-07T13:53:16-05:00

Rapid project results

As a company, we pride ourselves on not only our expertise in imaging, image analysis and 3D cell culture models and assays, but also our commitment to our Clients and close relationship with them. We provide our Clients with constant updates, rapid feedback and quick turn-around time on all project deliverables and see this as what truly separates us from other CROs. A typical contract research project will last anywhere between 2-6 weeks but for longer projects they can stretch out to 6 to 9 months depending on the specific endpoints.

Scientific communication

We find it incredibly important to develop a relationship with our Clients and to continually communicate to ensure that our projects meet our Client expectations and that any required changes are thoroughly discussed. During our projects, you will be in direct communication not with a business manager or project manager but the Scientific Director directly responsible for your project. This direct Scientist-to-Scientist communication allows us to quickly adapt on projects and ensure that you get results as quickly as possible. We see this approach as crucial to our team gaining a full understanding of the project scope so that we can provide recommendations to best meet the project’s desired end points.

There every step of the way

Many CRO’s have a transactional relationship with their Clients wherein the Client sends a sample and the CRO simply sends back a report once the project has been completed. We understand that during early stage drug discovery projects that many times things will not go exactly as they are planned and constant communication is required during this process to ensure that the project meets the Client’s expectations. During our projects we provide weekly updates and routinely will confirm that preliminary results align with what is expected so that we can determine if any changes are required to a project approach prior to executing the entire project. This can be as simple as determining to switch an antibody for labeling or as complex as changing a machine learning algorithmic approach for data processing.

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