The Future Feature, with Susan Wong | Read now

Medable, Inc caught up with noted Policy & Process expert, Susan W. , to discuss what she perceives as the biggest breakthroughs in clinical research to date, & what she thinks our industry should strive towards in the future.

Note: The opinions offered during this interview reflect the views of Susan Wong only, and do not represent those of Genentech, Inc.

What's one thing you wish everybody knew about your job?

I play a critical and contributory role in ensuring that clinical trials are conducted ethically, with patient safety as the top priority through the lens of ICH/GCP compliance with regulatory requirements. 

Additionally, my job in “Compliance” is needed to ensure we are identifying risks, due to the lack of adherence to regulations/processes during the execution (Sponsor/Site) of the clinical trial, and mitigating them to ensure we’re providing the highest quality (safety and efficacy) of approved pharmaceuticals to even ourselves (aka patients) as clinical trial-ists. 

We too are “patients”, and these pharmaceuticals that we are working on, we should realize that during the work we do with the execution and delivery of clinical trials - we too are the recipients of these medications, as well. 

In an ideal world, how would clinical research be done?

1. Clinical Research would be an option of treatment when no other available commercialized treatment has been approved, or if no other approved treatment works for the patient. 
2. More accessibility and easier to participate - via technology means. One portal for assessment, supported with Clinician knowledge and support. One portal to consent (harmonized protocol and documents) and to organize and deliver the study assessments, scheduling, etc with on demand support (medical, technology, supplies, etc,). 
3. Keep the studies separated: 

• Data modeling studies - Phase I/II/III 
• Human patient centric studies: Studies are architected in a way that provides the answers of efficacy/safety - Simplified.Studies that are architected for exploratory endpoints (perhaps Data Modeling). Studies that are for label extensions can be combined with exploratory. Studies that are for REMS programs can be combined with exploratory and continuous data collection. 

1. It would be conducted in a manner that would prioritize transparency, scientific rigor, and the highest level of ethical considerations which would be “blind” to diversity and inclusion - that is to say that those two aspects would be intuitively inclusive and not called out as an entity to be considered for inclusion (there is a difference). 

Key aspects that need to ideally be considered:

1. Research design - In addition to the current methodologies of design (RCT, Observational, etc), AI generated clinical trials models might mitigate the need to ascertain SAD, MAD, mechanism of action. 
2. Participant recruitment - To include patients in the study design using robust survey engines with Patient Advocacy groups to complete the surveys (asking how they manage their disease, compliance, co-morbidities, whether they would participate in a clinical trial (hybrid, all remote, in person), etc,..). 
3. Data collection and analysis - Access to data would be standardized, available, and transparent (non-monetary) to enable further hypothesis for research for indications. Patient demographics/genetics data to advance our ability to provide personalized medicine. 
4. Collaborative and reproducibility - Shared among researchers to foster scientific progress and studies architected as stated above #3. 
5. Safety monitoring: Continuously through personal devices and consent of patients who are taking approved medicines. 
6. Data modeling and data evidence based medicine - Phase I/II/III will be supplemented with evidence based assessment (data collaboration, molecule modeling etc) to support patient-centric studies based upon #3 above. 
7. Funding obtained ensuring independence and reduced influence of vested interests.

Enhancing the integrity and impact of clinical research overall. 

What's one barrier to research that's not being talked about enough?

Changing the way that clinical research is viewed such as “test tubes, experimentation", etc,.. 

Finding better ways using computer modeling and perhaps AI to have a better understanding of the molecules “mechanism of action” – so the perceived notion is that we’re experimenting on animals and people to better understand it. Utilize data modeling and computer intelligence to seek these answers early on and share it - how the landscape of science and medicine is evolving - to have trust. 

What's one consumer experience you wish you could bring to clinical research?

Mobile banking = Decentralized clinical trials (modern solutions/elements) for patient-centric studies. 

If the industry could just ______ things would work better.  Explain why.  

Invest in ourselves as human beings. 

1. Diversity and Inclusion – create silos and differences OR “we are people” “we are human beings”.
2. Succession in an empathetic manner.
3. Empathy and compassion towards each other.
4. You started from baseline (nothing) once.
5. Be teachers at heart.
6. Work with the best of intentions.
7. Have trust.

In your view, what is the smartest/best advancement in clinical trials that's happened in the past 5 years?

• Artificial intelligence (double edge sword).
• Decentralized Clinical Trials. 
• Prefilled syringes -simplicity, suitability for home use, reduction in wasted products, and greater dose precision. Pre-filled are convenient and help ease the administration process. Patient does not have to worry about the transfer of a drug from a vial to a syringe and therefore do not have to worry about leaving a small percentage of dose behind.

How will AI transform clinical research in the near future, and in the long-term?

See above