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Making N-of-1 Medicine a Reality

An SLAS Technology Special Issue captures a dramatic suite of advances in personalized and precision medicine. These new technologies address the treatment plans of individual patients with the hope of turning terminal illnesses into chronic issues. SLAS Technology Co-Guest Editor Dean Ho, Ph.D., found himself boiling down all of personalized and precision medicine (PPM) to one word during an SLAS-sponsored panel presentation held at InnovFest Unbound Singapore 2016. “When the moderator asked us to come up with one word to describe PPM, I said actionability,” he says.

“You need actionable technology that gets quick and accurate results and has the capability to continually do that for the duration of treatment,” says Ho. “Whether it’s dynamic dosing over time or dynamic combination therapy administration over time, actionability is what matters. We want to present patients with drug combination options that could truly turn this generation’s diseases from fatal to chronic.”

The June 2017 Special Issue of SLAS Technology (Translating Life Sciences Innovation) is called “Personalized and Precision Medicine: Making N-of-1 Medicine a Reality” and Ho describes it as an “A-to-Z guide for PPM. The issue focuses on key foundational advances that promise widespread implementation of PPM technology,” says Ho. “We include papers that cover everything the readers need to appreciate about what PPM encompasses and highlights ways to individualize care using methods that people don’t often think about or have never thought about before.”

The 11 peer-reviewed, original research reports from Switzerland, Sweden, Singapore, Spain and the United States delve deep into applications from using high-throughput screening (HTS) to access cystic fibrosis mutations and using cell culture assays to predict drug resistance in cancer therapy, to applying automated flow cytometry toward measuring pharmacological profiles in acute myeloid leukemia (AML), to analyzing multiple biomarkers for sepsis detection. Ho comments that “the selected papers in the special issue are highly relevant and very timely.”

Ho’s fellow Co-Guest Editor Ali Zarrinpar, M.D., Ph.D., agrees. “All of these frontiers are exciting,” says Zarrinpar, who recently joined the Division of Transplantation Surgery in the University of Florida College of Medicine as an associate professor. He was previously an assistant professor at the University of California, Los Angeles (UCLA) Medical Center Department of Surgery, Abdominal Organ Transplantation and Hepatobiliary Surgery, as well as an author of a review that appears in the special issue. “It goes back to what we used to describe as the art of medicine, in which every patient is different and the solution has to go by gestalt as to how that patient is treated. Precision medicine supports this art, and it brings more science into individualization of care.”

Taking Action

In reviewing manuscripts for the special issue, Ho and Zarrinpar examined both big data- and engineering-based approaches that offer practical treatment plans. “I think that is something unique from a lot of the newer technologies coming out,” Ho comments. “We also introduce the concept that data, both big and small, can be paired together to make personalized and precision medicine treatment approaches even more effective than we’ve ever thought possible.”

Zarrinpar is eager to reveal the wide spectrum of the technology available and show PPM’s progress, capabilities and applications. “When it comes to precision and personalized medicine, treating each patient individually is limited by the fact that there is so much to know about every individual and that every individual changes from day to day,” says Zarrinpar, who earned his medical degree and a Ph.D. in biochemistry at University of California, San Francisco (UCSF) and then completed a surgical residency and a transplant fellowship at UCLA.

Zarrinpar began working with Ho two years ago after learning about Ho’s work. As a professor of oral biology and medicine and bioengineering, as well as co-director of the Jane and Jerry Weintraub Center for Reconstructive Biotechnology at the UCLA School of Dentistry, Fulbright Scholar, SLAS Endowed Fellow, and former SLAS president and editor-in-chief of SLAS Technology, Ho had created a powerful phenotypic personalized medicine digital health platform that the duo wanted to use at the clinical level to optimize the immunosuppression dosing of Zarrinpar’s liver transplant patients.

Their research reveals that PPM technology outperforms the clinical standard, which consists of a physician reviewing a patient’s drug and dose history and giving the patient the next day’s dose based on an educated guess. The platform is more predictable, accurate and much less variable in terms of patients having medication levels that are too high or too low.

“Now we’re working on a couple of other projects, developing a defense system and different clinical scenarios – liver cancer, care for patients in intensive care settings, etc. – in which we can make effective and practical use of the PPM technology while improving healthcare in a straight forward way,” Zarrinpar says.

After proving that PPM is a positive divergence from clinical standards of care, Ho states that it’s time to act. “I think it’s time to converge and show what is possible using PPM paired with other approaches such as diagnostics that allow us to optimize patient care,” says Ho. “The special issue accomplishes this.”

Shaking Up Life Sciences Innovation

To launch the PPM topic, the special issue opens with a perspective from pharmaceutical and technology executive C. Katherine Wang, Ph.D., who suggests that the biotech and pharma industries need to find ways to increase the efficacy, efficiency and affordability of their products by tearing a page from the information and technology playbook.

In “Shaking Up Biotech/Pharma: Can Cues Be Taken from the Tech Industry?” Wang, who is also a member of the SLAS Technology Editorial Board, states that biotech and pharma should examine and reshape aspects of their companies such as operating with a small core team, investing less in conventional R&D infrastructure, shortening the product life cycle time and diversifying company leadership. “Merging these mindsets ultimately will result in more innovative and compelling products that come to market faster,” says Ho.

Moving into the heart of the collection is Zarrinpar’s study, “Metabolic Pathway Inhibition in Liver Cancer,” which examines whether the altered metabolic pathways in this cancer differ enough from the surrounding noncancerous cells to allow for the development of potent and specific compounds through clinical studies. In an interview for the June 2017 SLAS Technology podcast with David Pechter, M.S.M.E., Zarrinpar explains that blocking one pathway many times leads to resistance or increases in flow to other pathways. Optimizing combination therapy is the best approach to inhibit multiple metabolic pathways at once or by sensitizing tumors to chemotherapeutic drugs.

Zarrinpar wants to rethink how clinicians approach disease and its treatment. “As a liver transplant surgeon, I am interested in liver cancer, as well as transplantation technology and care of the transplant patient,” he says. “In medicine there are a lot of things that are not optimized and there’s a lot of variability between patients. Even the best patient cases have issues where that best possible care is less than ideal.”

Other evidence of the effectiveness of optimizing combination therapies is found in a paper by Dong-Keun Lee, Ph.D., et al., “Optimizing Combination Therapy for Acute Lymphoblastic Leukemia Using a Phenotypic Personalized Medicine Digital Health Platform: Retrospective Optimization Individualizes Patient Regimens to Maximize Efficacy and Safety.” Partnering with innovative clinician Vivian Y. Chang, M.D., a pediatric hematology oncologist at UCLA Mattel Children's Hospital, this team, which includes Ho, conducts a retrospective optimization using patient records to demonstrate how using a phenotypic personalized medicine platform results 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 the phenotypic platform individualizes care to optimize each patient's combination therapy regimen. Importantly, this study between Ho and Chang has opened the doors to giving pediatric cancer patients the best possible chance for optimized treatment outcomes, especially since PPM is a clinically proven technology.

From the Microtechnology, Medicine and Biology Lab of David Beebe, Ph.D., at the University of Wisconsin-Madison (UW-Madison) comes what Ho describes as “a key breakthrough in sample preparation for individualized lung cancer data analytics and management.” The team’s work, “Interrogating Bronchoalveolar Lavage Samples via Exclusion-Based Analyte Extraction,” by Jacob J. Tokar, et al., offers a strategy for earlier and better diagnosis through bronchoalveolar lavage (BAL), which provides a sample of lung tissue as well as proteins and immune cells from the vicinity of the lesion. A challenge to BAL effectiveness is diagnostic sensitivity, so the team developed an exclusion-based, solid-phase-extraction technique called SLIDE (Sliding Lid for Immobilized Droplet Extraction) to facilitate analysis of BAL samples.

An important study from researchers with the Cystic Fibrosis Foundation in Lexington, MA, reviews the urgent unmet needs for personalized medicine for the treatment of cystic fibrosis (CF). In “High-Throughput Screening for Readthrough Modulators of CFTR PTC Mutations,” Feng Liang, Ph.D., et al. develops HTS assays for two representative mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) premature termination codon (PTC). The team evaluates the feasibility of personalized therapy for CFTR PTC mutations Y122X and W1282X and discovers data that suggest personalization may not need to address individual genotypes, but that patients with different CFTR PTC mutations can benefit from the same medicines.

The special issue also offers a review by Eliza Li Shan Fong, Ph.D., et al., "3D Culture as a Clinically Relevant Model for Personalized Medicine." The research team from the National University of Singapore examines the current methods available for applying 3D culture systems toward personalized cancer research and drug development, as well as key challenges that must be addressed to fully realize the potential of 3D patient-derived culture systems for cancer drug development. Fong addresses how the 3D culture systems paired with patient-derived xenografts or patient-derived organoids may provide a more clinically relevant system to tackle issues presented by personalized or precision medical approaches.

Another review, “Current Trends in Multidrug Optimization: An Alley of Future Successful Treatment of Complex Disorders,” discusses the application of optimization techniques for the identification of optimal drug combinations. Written by Switzerland-based researchers Andrea Weiss, Ph.D., and Patrycja Nowak-Sliwinska, Ph.D., a member of the SLAS Technology Editorial Board, the study specifically focuses on the application of phenotype-based screening approaches in the field of cancer therapy. In their summary, the duo supports the view that phenotypic searches for drug combinations will lead the way to developing effective treatment regimens in oncology in the near future.

A meta-analysis, “Predictive Value of Ex Vivo Chemosensitivity Assays for Individualized Cancer Chemotherapy,” by Kristin Blom, et al., a research group from Uppsala University, provides an up-to-date literature meta-analysis on the predictive value of ex vivo chemosensitivity assays for individualized cancer chemotherapy and discusses their current clinical value and possible future developments.

“Continuous Adaptive Population Reduction (CAPR) for Differential Evolution Optimization," by Ieong Wong, Ph.D., et al., proposes an adaptive population-sizing method for the differential evolution (DE) algorithm. Researchers in a joint effort between the UCLA Henry Samueli School of Engineering and Applied Science and the School of Biomedical Engineering, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, reveal how using CAPR dynamically and continuously reduces the population size in response to the drug combination optimization progress. In CAPR, the population size reduction rate is dependent on the gradient of optimization performance, while the population reduction size is not a constant but a variable based on the performance of the current and previous iterations.

In "Drug Discovery Testing Compounds in Patients Samples by Automated Flow Cytometry," Pilar Hernández, Ph.D., and a team from Vivia Biotech in Madrid, Spain, develop an automated flow cytometry platform for drug screening to address functional ex vivo assays that predict a patient’s clinical response to anticancer drugs The platform, called PharmaFlow, evaluates multiple endpoints with a robust data analysis system that can capture the complex mechanisms of action across different compounds as it tests peripheral blood or bone marrow samples from patients diagnosed with hematological malignancies. In addition, relevant biomarkers can be identified that determine the patient’s sensitivity, resistance or toxicity to a given treatment.

Authors from the Department of Bioengineering, University of Texas at Dallas Anjan Panneer Selvam, Ph.D., and Shalini Prasad, Ph.D., who also is a member of the SLAS Technology Editorial Board, used "Companion and Point-of-Care Sensor System for Rapid Multiplexed Detection of a Panel of Infectious Disease Markers" to highlight their nanochannel-based electrochemical biosensor that has been demonstrated for rapid and multiplexed detection of a panel of three biomarkers associated with sepsis. The label-free biosensor detects procalcitonin (PCT), lipoteichoic acid (LTA) and lipopolysaccharide (LPS) from human whole blood. This novel technology has promising preliminary results toward the design of sensors for rapid and sensitive detection of the three panel biomarkers.

Zarrinpar believes that these papers represent the dynamic diversity in life sciences discovery and technology. "These topics show the investigators' interests. Having this special issue and having the freedom to choose a topic within this focused spectrum is exciting and interesting," he comments.

Ho also found the papers to be motivating. "We look at therapeutics and diagnostics from a wide range of very talented research groups from all over the world. This is what the journal tries to achieve all the time," he comments.

Interdisciplinary Collaboration

Ho states that to bring a field such as precision and personalized medicine into widespread use requires a bridge between research in academia and industry. “The way that drugs and drug combinations are designed, developed and moved through clinical trials is understandably based on the regulatory environment,” he says, adding that this process takes decades to accomplish.

“PPM is an opportunity to dramatically advance and redefine how new therapies develop in partnership with clinicians to see if the drugs are actually working, in a shorter time span,” Ho continues. “It’s important to get out of the shell of how drugs are developed conventionally.”

Zarrinpar agrees, commenting that it is important to fundamentally rethink how precision medicine is applied and verify that it works. "There is a prevailing attitude that there is no return on the investment to develop something for one person or a few people,” he says. "Drugs are extremely expensive to develop. That’s almost a disincentive to search and produce a precise individualized drug or combination.”

Ho believes that SLAS Technology’s focus on translational and applied research is a great launching pad for this topic. “I think that 10 years ago we wouldn’t have seen as many papers that look at diagnostics being conducted on actual patient samples and taking patient data to optimize combination therapy,” he says.

"Over the course of its more than 20 years of publication, SLAS Technology has been quite effective at highlighting emerging technology," Ho continues. "In a typical year, the regular issues of SLAS Technology cover everything from robotics, nanomedicine and microfluidics, to optimizing combination therapy and novel diagnostic and imaging strategies. What’s interesting is that all these topics play an important role in the N-of-1 medicine platform.”

Learn More in the June 2017 Special Issue of SLAS Technology

The SLAS Technology special issue on N-of-1 Medicine features 11 original research reports from Switzerland, Sweden, Singapore, Spain and the U.S., and is available now at SLAS Technology Online for SLAS members, SLAS Technology subscribers and pay-per-view readers. Free public access becomes available one year after final publication.

June 5, 2017