High-end Software Solutions in Clinical Research
Clinical trials are the most important aspect of every new drug roll out. It is the period when the drug is tested and verified with a selected group of patients, carefully chosen among a large pool of people. Pharma companies usually allocate big budgets for this phase as it is when the drug’s actual effect is tested out.
Thanks to clinical trials, pharma companies can properly plan the production rate of the new product, outline side effects, effectiveness and how patients and clinics adopt the new product. It is also the most complex part of the drug roll-out, with many complex protocols to follow. As clinical trials have become more and more a focus of attention to many, here are some of the critical aspects to ensure that the clinical trial process is successfully managed and achieves its goal to the maximum.
Aspect 1: Having Clear Guidelines and Communicating Them to All Parties
Due to the nature of its complexity, the clinical trial process involves many cross-functional teams and guidelines, all of which have to be communicated in a simple yet informative way. The number one objective of every study is to have a clear goal and mutual understanding among all parties involved. All information about the study has to be signed off by the pharmaceutical company so that the agencies involved in the patient selection or execution of the trial should follow a predetermined scenario to ensure that all the study parameters are taken into account. This also makes it easy to track the progress of the trial and how successful it has been in complementing the predefined steps. Having several parties involved in a single process makes it also hard to communicate and follow the protocol.
When protocols are complex, they usually require a lot of documentation and time to go through all the steps. Doctors have a particularly high schedule, and for them, it is hard to allocate a ba significant amount of time. That is why it is essential to have a well-structured protocol with synthesised information, covering all the aspects of the trial. How technology can assist in this case is to have a very carefully and pragmatically designed platform where all the different stakeholders can find information tailored especially for them. Seeing all the steps from the protocol in a visually appealing way would firstly engage participants much more and will give them the feeling that they know the objective and can easily identify the value of the trial.
This platform can be used as an active information pusher from the pharmaceutical company to the agency or hospital facility. The form of “push notifications” attracts a lot of attention and is usually followed by an action from the user’s side. Even if there are any institutional changes or news, this platform can be integrated via API with news providers to generate and distribute vital information.
Once you have all the protocol steps outlined, over time, it will turn into a standard practise to have such a structure for future clinical trials. In other words, having such a platform would introduce a new, standardised way of communicating the trial’s strategy and would be applicable for any time of trial, no matter the specific drug.
Aspect 2: Find the Right Audience
The second critical aspect of a clinical trial is to find suitable patients to assess and evaluate the new drug. Before patients agree to participate in a clinical trial, they need to be aware of the whole clinical protocol. Patients often rely on receiving information via a partnering agent or the CRO, which in some cases can cause miscommunication and outdated information. Having one centralised platform (as mentioned in Aspect 1) where patients can browse for themselves the clinical trial protocol will increase the credibility and accuracy of information as all of the steps and protocols are coming directly from the pharmaceutical companies.
I remember that several years ago, my doctor called me and asked me if I wanted to participate in a clinical trial for a new stomach drug, as I was having severe gastritis back then. I refused to join because no information was provided to me. Prior to making my decision, everything was verbal, and there were no materials or defined steps for my participation. For sure many of the readers have been in such situations or have been in the other shoes: receiving many rejections for participation in a trial. I would say that the biggest impact for me would have been:
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To receive an objective justification why I was selected
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To be given clear information on what the protocol and end goal will be
Concentrating on the first point, selecting the candidates for a trial is the key to achieving the trial’s goal. It is not an easy task, especially when trials are simultaneously performed in several countries and involve a short timeline. Not selecting the right audience is probably among the top 3 reasons why many clinical trials fail. Here comes the natural question: how can technology help avoid past mistakes and ensure a stable pool of trial candidates.
Exploring this topic, there is one new way that can make a drastic change in this field: secret computing. I will talk a lot about “secret computing” as it is a good fit for the clinical trial case. To evaluate the whole pool of candidates, you need to have the appropriate data to do so, especially data collected from different sources: laboratories, different hospitals, and CROs. Sometimes some sources are not allowed to share their patient’s data due to privacy regulations. What secret computing does is aggregating all the data across different locations and institutions, computing it but still preserving the patient’s personal information anonymity. This opens a huge opportunity for creating more accurate and bigger pools of candidates, now that analysing different data is made possible. Such an approach minimises the risk of not selecting suitable candidates or missing out on an important group that would impact the trial.
Aspect 3: Creating a Close Patient Relationship and Executing the Trial
Besides finding suitable candidates, attracting them is another critical point. Many trials are said to discontinue due to a lack of interest or persistence from patients. And it is understandable: without a proper engagement, patients might lose interest rather quickly. The key to a good engagement is creating and maintaining a good and stable relationship between the patients, doctors and the CROs. Such a relationship should not limit itself to the transactional side of the process: only input of data and that it is. We have seen in our experience creating digital health platforms that patients should always be engaged and approached in a proactive way. This is how you create a sense of common goal and value added to the process. Poor retention in patient engagement along the trial process results from a lack of communication between the doctors and a lack of knowledge of the protocol steps.
How we can address that via technology is by simply creating a communication channel between the two parties: doctors and patients. Having a chat, which also serves as a case management platform, will give that sense of immediate connection to the other party and build trust. Advanced chat platforms also have the functionality to schedule activities and send automatic push notifications, which can all be very useful in executing and tracking the trial. On the one hand, it would save time for doctors and remind patients that they need to complete their tasks on time. On the other hand, such a platform will help patients if they lose track of the progress. Knowing what is expected from the patient and giving them the ability to ask questions or post comments at any point will most likely increase retention and create a loyal relationship.
Aspect 4: Data Analytics
Assuming that we have found the right candidates and they have been fully engaged, the next step is to analyse all the data and make respective recommendations. Aggregating data from many users and institutions requires a special approach as sometimes there are legal and geographical restrictions to access and combine data from various locations. This leaves a significant gap in the last and most anticipated part: understanding the results.
Here, again, secret computing can come and perform the necessary task. Due to its nature of privacy-preserving computation, all different sources of data can be interconnected and analysed. By using secret computing and pre-defined criteria also data quality can be addressed. Some inputs that might be incomplete or incorrect (something that can be initially monitored via the communication platform) will be addressed so that the results are not manipulated incorrectly.
Once the data is analysed, it has been presented in a visually appealing way along with the right concussions and recommendations. This can be a natural extension of the communication platform and visible only to a certain group of people. Having the ability to also do predictions or secondary analysis on a more specific group of people will add more value to the results. Here frameworks such as machine learning and artificial intelligence can be utilised, as the models will be trained with the aggregate data and plotted on future scenarios and variables.
The number of clinical trials over the years has increased exponentially, so the need for a unified and holistic approach to the protocol is needed more than ever. Innovative technology can be used in almost every aspect of the process: from defining and communicating the goal and protocol to patient recruitment, execution, and analysis. Having that in one platform which is easily integratable to 3rd party software and is creating valuable relationships can boost the performance of the trials and speed up the process.
