Publications

NU TechRep #2105: SDP-SF Workshop Notes May 3-4, 2021

Authors: Mansoor Amiji, Walter Gabriel, Ioannis Kakadiaris, Nikos Passas, Ravi Sundaram & Muhammad Zaman

This is a compilation of the notes from the 2-day SDP_SF Workshop held, virtually, on Monday May 3 and Tue May 4, 2021.

The workshop brought together partners from diverse backgrounds with whom the Find-M (Financial Network Disruptions in Illicit and Counterfeit Medicines Trade) team have been collaborating since 2020 to document challenges and opportunities for sensing, disrupting, and preventing the trade in substandard/falsified medical products. The participants came from a variety of institutional and organizational backgrounds – pharmaceutical companies, medical device makers, regulatory and law enforcement agencies, international organizations, academies and universities – and represented a range of different disciplines – life sciences, legal, computer science, law enforcement, bio-engineering, cryptography, public health, etc.

The first day began with Dr Wendi Nilsen, National Science Foundation giving the keynote speech and the second day opened with Prof. Paul Newton, Oxford University as the keynote speaker. On each of the days the keynote speeches were followed by three panel discussions moderated by members of the FIND-M team. Each session started with 2-minute answers by each panelist to three questions, before being opened up for discussion. Each panel session lasted about 50 minutes.

On the network you keep: analyzing persons of interest using Cliqster

Authors: Saber Shokat Fadaee, Mehrdad Farajtabar, Ravi Sundaram, Javed A. Aslam & Nikos Passas

Our goal is to determine the structural differences between different categories of networks and to use these differences to predict the network category. Existing work on this topic has looked at social networks such as Facebook, Twitter, co-author networks, etc. We, instead, focus on a novel dataset that we have assembled from a variety of sources, including law enforcement agencies, financial institutions, commercial database providers and other similar organizations. The dataset comprises networks of persons of interest with each network belonging to different categories such as suspected terrorists, convicted individuals, etc. We demonstrate that such “anti-social” networks are qualitatively different from the usual social networks and that new techniques are required to identify and learn features of such networks for the purposes of prediction and classification. We propose Cliqster, a new generative Bernoulli process-based model for unweighted networks. The generating probabilities are the result of a decomposition which reflects a network’s community structure. Using a maximum likelihood solution for the network inference leads to a least squares problem. By solving this problem, we are able to present an efficient algorithm for transforming the network to a new space which is both concise and discriminative. This new space preserves the identity of the network as much as possible. Our algorithm is interpretable and intuitive. Finally, by comparing our research against the baseline method (SVD) and against a state-of-the-art Graphlet algorithm, we show the strength of our algorithm in discriminating between different categories of networks.

Combinatorial approach in the design of multifunctional polymeric nano-delivery systems for cancer therapy

Authors: Amit Singh, Meghna Talekar, Thanh-Huyen Tran, Abishek Samanta, Ravi Sundaram and Mansoor Amiji

There have been significant advances in our understanding of cancer as a disease at the molecular level. Combined with improved diagnostic systems, the concept of personalized medicine was introduced where therapy for every patient can be customized according to their disease profile. The nanotechnology approach for formulation design and the advent of drug delivery systems for small molecules and biologics has contributed to the development of personalized medicine. Despite the progress, effective management and treatment of cancer remains a clinical challenge. The majority of drug delivery vectors that have undergone clinical trials have been discontinued prematurely because of poor therapeutic outcomes, off-target effects and non-specific toxicity due to the components of the formulation itself. Therefore, there is an urgent unmet requirement for a systematic approach to design drug delivery vectors that not only deliver the cargo to the desired site of action, but are also highly biocompatible and non-toxic. The past decade has seen the evolution of a combinatorial approach to drug delivery, a concept that has been classically successful in drug discovery research. In the present review, we summarize the wet-lab and in silico strategies to designing libraries of biocompatible delivery materials using combinatorial chemistry and support this strategy with pre-clinical success stories in cancer therapy.

Bitter Pills: The Global War on Counterfeit Drugs

Authors: Muhammad H. Zaman

Long the scourge of developing countries, fake pills are now increasingly common in the United States. The explosion of Internet commerce, coupled with globalization and increased pharmaceutical use has led to an unprecedented vulnerability in the U.S. drug supply. Today, an estimated 80% of our drugs are manufactured overseas, mostly in India and China. Every link along this supply chain offers an opportunity for counterfeiters, and increasingly, they are breaking in. In 2008, fake doses of the blood thinner Heparin killed 81 people worldwide and resulted in hundreds of severe allergic reactions in the United States. In 2012, a counterfeit version of the cancer drug Avastin, containing no active chemotherapy ingredient, was widely distributed in the United States. In early 2013, a drug trafficker named Francis Ortiz Gonzalez was sentenced to prison for distributing an assortment of counterfeit, Chinese-made pharmaceuticals across America. By the time he was arrested, he had already sold over 140,000 fake pills to customers.

Even when the U.S. system works, as it mostly does, consumers are increasingly circumventing the safeguards. Skyrocketing health care costs in the U.S. have forced more Americans to become “medical tourists” seeking drugs, life-saving treatments and transplants abroad, sometimes in countries with rampant counterfeit drug problems and no FDA. Bitter Pills will heighten the public’s awareness about counterfeit drugs, critically examine possible solutions, and help people protect themselves. Author Muhammad H. Zaman pays special attention to the science and engineering behind both counterfeit and legitimate drugs, and the role of a “technological fix” for the fake drug problem. Increasingly, fake drugs affect us all.

Network Effects of Risk Behavior Change Following Prophylactic Interventions

Authors: Rajmohan Rajaraman, Zhifeng Sun, Ravi Sundaram, Anil Kumar S. Vullikanti

We formulated a network-based model to understand how risk behavior change in conjunction with failure of prophylactic interventions can lead to unintended outcomes where “less (intervention) is more (effective).” Our model captures the distinction between one- and two-sided risk behavior change. In one-sided situations (e.g. influenza/H1N1) it is sufficient for either individual in an interaction to exhibit risk behavior change whereas in two-sided situations (e.g. AIDS/HIV) it is necessary for both individuals in the interaction to exhibit risk behavior change, for a potential transmission of the disease. A central discovery is that this phenomenon occurs at differing levels of intervention coverage depending upon the “sidedness” of the interaction. We find that for one-sided interactions, sufficiently high vaccination coverage is necessary for mitigating the effects of risk behavior; for two-sided interactions, it is essential to combine prophylactic treatments with programs aimed at reducing risky behavior. Furthermore, again dependent on the “sidedness,” targeting highly connected nodes can be strictly worse than uniformly random interventions at the same level of coverage.