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Redefining Drug Development with Digital Health and Nanomedicine

As the first SLAS Endowed Fellowship draws to a close, SLAS Innovation Award Finalist Dean Ho and his team of researchers at UCLA introduce a landmark advance in personalized and precision medicine in the challenging area of combination drug therapy.

“Pinpointing the right drug and dose for each person at any given time is like finding a needle in 10 galaxies,” says Dean Ho, Ph.D., professor of oral biology and medicine, and bioengineering, as well as the co-director of the Jane and Jerry Weintraub Center for Reconstructive Biotechnology at the University of California, Los Angeles (UCLA) School of Dentistry. “In a situation as complex as designing a novel combination therapy for cancer or infectious diseases, the number of possible drugs and dosages is almost infinite.”

To conquer this enormous research space, Ho and colleagues developed a powerful technology platform that optimizes combination therapy by mapping the relationship between drug dosages (input) and patient response to that dosage (output). Supported by funding that included a five-year, $100,000 grant from an SLAS-established Endowed Fellowship that launched in 2012, Ho’s lab calls this platform Phenotypic Personalized Medicine (PPM).

“The output can be anything that we want to target, from the size of a tumor using imaging, to markers in the blood such as bacterial or viral load and/or toxicity. It is anything quantifiable that is a reflection of how well the treatment is progressing,” says Ho. The PPM input-output calibration then can be visualized by constructing patient-specific drug interaction maps to pinpoint the best drug-dose ratios during the entire course of treatment to achieve the desired patient response, an unprecedented advance.

“PPM technology allows us to produce individualized, three-dimensional phenotypic maps that constantly reveal how the patients are responding to complex treatments. These maps pinpoint the drug ratios that will result in optimal treatment outcomes,” explains Ho. “Based purely on clinical data from the patient, the maps continuously change throughout the course of treatment as the patient’s physiology reacts and changes over time. Our technology platform is not an algorithm or model of how humans respond to therapy. We’re not trying to predict, cross our fingers and hope for the best. There’s no guess work involved.”

Ho’s research team and collaborators have already demonstrated that PPM can optimally treat virtually any disease, as the new technology does not require pre-treatment knowledge of disease mechanisms, or the genomic or pharmacokinetic profiles of each patient. “This is important information, but it is not required to optimize care with PPM,” Ho continues.

“Studying an entire genome for mutations and abnormalities may help pinpoint which drug will work better for an individual, but you still don’t know the dose to give,” Ho says, adding that giving multiple drugs complicates the process substantially. “Picking a drug and giving it at the wrong dose alongside another drug at the wrong dose can effectively make treatment useless or even harmful. Furthermore, the optimal drug ratios can change constantly within a single patient.” Finding a solution takes time and funding.

Supporting Research: From Nanodiamonds to PPM

The SLAS Endowed Fellowship awarded to Ho was the predecessor to today’s SLAS Graduate Education Fellowship Grant. “This SLAS Fellowship allowed us a unique opportunity and freedom to explore what we wanted without specific restrictions on the type of research we could do, or the type of person I could hire or the supplies or equipment I needed,” explains Ho, who has been involved in many facets of SLAS over the years, having served as president, board member and editor-in-chief of the Journal of Laboratory Automation (JALA), now known as SLAS Technology. Most recently Ho served on the Society’s Nominations Committee.

“We never imagined this fellowship would play such an important hand in allowing us to treat patients,” Ho mentions. “Through the Society, we connected with collaborators we needed to advance our work. SLAS is a different organization because of its connections throughout industry, academia and government. It is catalytic in getting technology applications to the patient.”

When the SLAS Endowed Fellowship launched in 2012, Ho was newly appointed to his post at UCLA, having just moved from Northwestern University, where he was an associate professor in the departments of biomedical and mechanical engineering. “I credit so much of where I am today to the amazing community at Northwestern,” he says. “I had a chance to explore the basic aspects of cancer treatment, developing new drugs and nanotechnology. The move to UCLA marked the beginning of when my research evolved into translational work. The opportunity to treat patients directly was important.”

In the earliest days of the endowment, Ho worked in collaboration with Professor Cun-Yu Wang, D.D.S., Ph.D., the No-Hee Park Endowed Professor and Chair of Oral Biology and Medicine at the UCLA School of Dentistry, and a member of the National Academy of Medicine. The team explored the use of nanodiamonds to treat oral cancer. These carbon-based nanoparticles proved to be exceptionally useful for binding compounds, which resulted in the efficacy and safety of treatment for a broad spectrum of diseases ranging from cancer to infectious diseases.

“Nanodiamonds are very promising drug delivery agents,” Ho explains. “However, both nanotechnology-modified and conventional unmodified drugs are often best used in combination, where multiple drugs are co-delivered to address many disease pathways at one time. Optimizing combination therapy, which involves using the most ideal drugs as well as identifying the right dose of each drug has thus far been a major challenge for the entire pharmaceutical industry.” Developing a technology to optimize combination therapy, therefore, became another goal of his research.

To achieve this, Ho united an extraordinary team of collaborators that included his father, Chih-Ming Ho, Ph.D., the Ben Rich-Lockheed Martin Professor in the UCLA School of Engineering, who pioneered one of the original technologies at the foundation of PPM, previously known as Feedback System Control.II (FSC.II). FSC.II revealed relationships between input and output data and became the precursor to more powerful PPM technology platforms. The advent of PPM was a game changer for the team. They used it to develop and study new drug combinations with nanodiamond-modified cancer drugs for optimal breast cancer treatment. 

The resulting published study found that FSC.II-optimized drug combinations that used nanodiamonds were safer and more effective than optimized drug-only combinations. Optimized nanodrug combinations also outperformed randomly designed nanodrug combinations. That was followed by studies with multiple collaborators who validated this approach in animal studies that involved many other types of cancers, as well as infectious and other diseases

In April 2016, the team announced the results of using PPM in conjunction with prospectively treating liver transplant patients. “With the liver transplant trial, we recruited eight patients: four were control patients treated using a conventional approach and four patients were treated using PPM,” says Ho, adding that the team collaborated closely with Ali Zarrinpar, M.D., Ph.D., a UCLA liver transplant surgeon and also an SLAS Technology Editorial Board member. The team examined the large number of immunosuppressant drugs liver transplant patients receive after their surgery to prevent rejection of the new organ and targeted a specific phenotypic outcome for each patient. The goal was to keep the immunosuppressant drug tacrolimus within a narrow, patient-specific target range in the blood, continuously.

“For some of these patients, the tacrolimus level in their blood is all over the place. It’s jumping up and down, constantly residing outside of the target range,” Ho explains. “One patient in the control group was out of range 90 percent of the time. If the level of tacrolimus is too high, the patient can experience seizures and other forms of nervous system toxicity. If the levels are too low, the patient may reject the organ.”

The standard of care in such instances is to drop the dosage when the level gets too high. “There’s so much going on with these patients,” says Ho, “they have a new organ in their body, they are on other medications to treat infections from the surgery, and on and on. If you drop the dose of the immunosuppressant, the next day the levels are even higher. Other times, it will bottom out completely.” PPM allowed the team to create a phenotypic map to identify the optimal dosage for each patient. “Our PPM-treated patients observed 50 percent fewer substantial deviation events compared to those of the control patients,” Ho reports.

Another aspect the team explored was how much time the transplant patients spent in the hospital. “It’s not a standard measure of how effective treatment is, but for us, this discharge data gave us a good idea of whether or not PPM implementation could positively impact the healthcare system,” says Ho. “We found that patients treated with PPM technology were discharged on average three weeks earlier than patients using the current standard of care. One can imagine what that was like to realize our technology enabled patients to spend less time in an ICU, reduced their chance of infection and gave the insurance companies a three-week cut in costs.”

Ho’s team and colleagues have completed more than 30 studies that have demonstrated PPM’s ability to pinpoint the best care for a broad spectrum of disease indications. “I think that’s the biggest achievement,” Ho says. “The results showed that PPM works in cells, animals and patients, and we are now in the process of initiating new PPM studies towards pediatric leukemia and other disorders.”

Sharing Results and Expanding the Work

Ho shared how this next phase of PPM unfolded at SLAS2017 in his presentation, "Optimizing Clinical Combination Therapy Using a Phenotypic Personalized Medicine Technology Platform,” one of nine presentations for the 2017 SLAS Innovation Award. The presentation highlighted PPM’s move into research regarding acute lymphoblastic leukemia (ALL), one of the most common types of cancer in children. In addition to sharing results of the ALL study, Ho addressed PPM approaches to develop combination therapies and nanotherapies for oncology, infectious and metabolic disease, as well as other indications, and how they have resulted in markedly improved clinical treatment outcomes.

“I discussed the ability to continuously optimize and personalize the administration of multiple drugs, the challenges of current leukemia combo therapy and combo therapy in general,” Ho says of the presentation, which he also published as a paper in the June 2017 issue of SLAS Technology.

The research behind Ho’s SLAS Technology paper and SLAS2017 presentation is a retrospective optimization using patient records to demonstrate how using PPM would have resulted in better treatment outcomes compared to conventional treatment of pediatric leukemia. The study differs substantially from conventional retrospective analysis in that regular analysis tries to correlate large sets of data to look for trends that exist, while this study reveals how PPM individualizes care to optimize each patient's combination therapy regimen.

Conventional chemotherapy for pediatric leukemia consists of treatment phases that last two to three years from diagnosis. The goal of the prolonged maintenance phase of the treatment is to prevent disease relapse and includes recurring cycles of many drugs. This traditional course can cause many side effects, including life-threatening infections. Dosing is frequently adjusted through a system of trial and error, which is not always accurate.

In addition, conventional therapy for oncology often directs clinicians to use the maximum tolerated dose (MTD). “While administering one drug at the MTD may result in higher efficacy, toxicity will likely be higher, too,” comments Ho. “When two drugs are used, the MTD approach no longer holds true. These drugs interact. One can’t just administer the highest dosages possible and hope to have the best outcome. In fact, administering combination therapy at the MTD has resulted in major clinical trial failures and patient mortality. Conventional approaches simply cannot find the optimal drug ratio. What’s more, our PPM technology has prospectively shown that the combinations that are currently used in the clinic are almost always far from optimal.”

The research team’s goal in the study was to show how PPM could pinpoint drug dosages that would result in better treatment outcomes. “Kids have their whole lives in front of them. If we can shorten this treatment to reduce the long-term complications or fatal infections, that’s a game changer,” Ho says. “While the five-year survival rate for pediatric ALL is fairly high, there is still a subpopulation of kids whose chemotherapy dosing is difficult to manage. For this group, one of the phenotypic targets is to maintain a specific level of white blood cells. If the count gets too low, there can be major infection. There are children with this cancer who have good prognoses, but then because their immune system is so compromised from treatment, they actually end up dying from infections.”

When comparing data of dosages patients should have received during the course of care to those actually received in the clinic, results “were often very different,” Ho reports. “Generally, the PPM map of the optimum dose was lower than the doses given in each patient’s historical record. This data shows that we can maintain or improve the patient’s care with a much lower dose. We no longer have to rely on successively escalating the dose to find the highest possible dose the patient can tolerate. We can do much better than that. Importantly, PPM is already clinically validated for multiple indications. Therefore, these retrospective optimization studies provide key insight into how we will design our forthcoming prospective ALL clinical trial.”

Currently, prospective PPM trials for the treatment of tuberculosis and HIV are ongoing, with a blood cancer trial on the horizon. “PPM is universally applicable to every disease and every patient on the planet,” Ho comments. “It’s important to harness this important technology to overcome many of the treatment barriers that have persisted in the clinic for decades. We’ve seen cases where patients’ drugs are antagonistic for the entire duration of care, unbeknownst to the clinical team. They were using a conventional standard of care based off of decades-old clinical trials.”

He applauds innovative clinicians, such as Zarrinpar during the liver transplant trial and Vivian Y. Chang, M.D., the pediatric hematology oncologist at UCLA Mattel Children's Hospital, with whom the team worked during the leukemia treatment optimization study.

“Successfully implementing PPM in the clinic, either for personalized treatment or the administration of a novel combination therapy regimen was based on a progressive mindset from our team members from the medical and engineering communities,” Ho says. “They understand this technology and what it has already done to optimize treatment for so many diseases.”

March 13, 2017