Please save the date to join your colleagues in the Connecticut business development community on September 11, 2012 in New Haven for presentation on the methods, uses and challenges of early-stage IP valuation in biopharma. Stakeholders in all stages of drug development, business development and licensing will learn best practices exemplified through real-world case studies.

This talk will be given by David Greenwald, PhD. from Relay Technology Management. David Greenwald holds a Ph.D. in Genetics from Tufts School of Medicine and is an active member of the Boston chapter of the Licensing Executive Society. Relay Technology Management is a life sciences trend analytics and asset valuation software provider.

You will also have an opportunity to network with your colleagues. Please forward this to any colleagues who may be interested.

Connecticut Chapter of the Licensing Executives Society

September 11, 2012
6:30PM – 9:30PM

Harkness Lounge in Harkness Hall
Yale School of Medicine
367 Cedar St
New Haven, CT

Discussion:

‘The Methods, Uses and Challenges of Early-Stage IP Valuation in Biopharma’

Speaker
David Greenwald, Co-founder & Managing Director, Relay Technology Management LES USA & Canada Regional Vice President for USA

Dr. Greenwald, co-founder of Relay Technology Management, Inc., currently serves as Managing Director. Previously, Dr. Greenwald was an Associate Investigator at the Naval Medical Research Center in Silver Spring, MD. While there, Dr. Greenwald worked with the Food and Drug Administration (FDA) on 510(k) applications for diagnostic devices for dengue fever. Dr. Greenwald was a Howard Hughes Medical Institute (HHMI) research fellow while earning a B.S. in Cellular Biology and Molecular Genetics from the University of Maryland, College Park. He was awarded an NIH Ruth L. Kirschstein National Research Service Award (NRSA) towards his Ph.D. research dissertation on gene therapy for Retinitis Pigmentosa. Dr. Greenwald focuses on infectious diseases, cancer and genetics. He is an active Licensing Executive Society member.

Location
Harkness Lounge in Harkness Hall
Yale School of Medicine
367 Cedar St
New Haven, CT

Schedule
Reception: 6:30PM to 7:30PM
(bar, hors d’oeuvres and light buffet)

Program: 7:30PM to 8:30PM followed
by coffee & dessert

Costs and cancellation policies
$40 LES members in advance (payment received by Friday, September 7th)
$50 Non-members in advance (payment received by Friday, September 7th)
$25 Students in advance (payment received by Friday, September 7th)
$50 LES members at the door
$55 Non-members at the door
$35 Students at the door
Cancellations made after 5:00pm EDT, September 10th cannot be reimbursed, but substitutions are welcome!

Registration and payment options

1) Online registration will be announced in a few days

2) To register and pay by check,

Send e-mail to LES-CT@compass-grp.com and include: your name, title, company, phone & e-mail address
Make check payable to “LES” with the memo “CT Chapter September 11th, 2012”
Mail check and your business card to:
LES CT Chapter
c/o Compass Strategic Consulting, Inc.
129 Church Street, Ste 614
New Haven, CT 06510
For more information about this event and the LES Connecticut Chapter, contact:
Paul Gallagher, LES CT Chapter
203.777.9570
pgallagher@compass-grp.com

Directions to 367 Cedar St., New Haven, CT

View Map

From I-95 North or South
I-95 traveling north or south Exit 47 to Route 34 west to Exit 2. Turn left on College Street and cross over rt. 34. College turns into Congress. Turn right onto Cedar (light). Harkness is at the end of the block just before York Street.

From I-91 South
Take I-91 south to exit 1, which will put you on Route 34. Follow directions as from I-95.

A map of the Medical School area with driving directions and more is here.

Parking: Free street parking is available on College, Congress, or Cedar Street after 7pm but can be hard to find (parking on College and walking down Cedar is the best bet.) The Air Rights Garage has parking available; turn right on York from Cedar, then left on Frontage, left on Park, left on Frontage the other way, and there is an entrance there, right before York Street. The second-floor walkway will take you over to the hospital; cross York to get to the Med School.

Train Schedules

Both Amtrak and Metro-North trains stop in New Haven’s Union Station.

• Aaron Sandoski, Managing Director, Norwich Ventures
• Ankit Mahadevia, Principal, Life Sciences group at Atlas Venture
• Anupendra Sharma, Partner, Siemens Venture Capital
• Darshana Zaveri, Partner, Catalyst Health Ventures
• David L. Lucchino, CEO, Semprus Biosciences
• Guy Fish, VP, Healthcare Practice Group at Fletcher Spaght Ventures / Consulting
• John Fletcher, Founder & CEO, Fletcher Spaght Ventures / Consulting
• Kevin Bitterman, Principal, Polaris Venture Partners
• Lawrence Wittenberg, Partner, Goodwin Proctor
• Maggie Pax, Vice President of Business Development, MicroCHIPS
• Mark Namchuk, Head of Cambridge Research, Vertex Pharmaceuticals
• Nandini Murthy, Principal, ENEM Consulting
• Sameer Sabir, CEO, MoMelan Technologies
• Steven Tregay, Founder, President & CEO, FORMA Therapeutics

Relay TM’s Un-partnered Alzheimer’s Assets Explorer

Welcome to the Relay’s Technology Management’s Un-partnered Alzheimer’s Assets Explorer. This interactive visualization tool is intended to help users explore the pre-clinical, phase I and phase II Alzheimer’s Assets that are *un-partnered. Below is a brief description of the visualization followed by more technical details of the analysis.

Use the filters on the right hand side of the dashboard to search by Route of Administration, Phase of Development, Mechanism Target, and Country Headquarters of the primary asset holder.

Technical Details:

Sophisticated data mining algorithms were developed to generate this dashboard’s underlying data. Over 20 million scientific, medical and business documents are continuously analyzed by the Relay Innovation Engine to power this interactive dashboard.  The Relay Innovation Engine is a unified, real-time trend monitoring and comparative asset analysis platform, which helps business development professionals in the life sciences industry identify new licensing opportunities and assess the relative attractiveness of assets under consideration. Specifically, the Relay Innovation Engine can be used to confirm the attractiveness of assets under consideration, and unearth new technologies that have high probability of return.

Welcome to the Epigenetics Drug Target Explorer. This interactive visualization tool is intended to help users explore the trends and therapeutic interested associated with the set of 279 proteins referenced by the recent Nature Reviews Drug Discovery Article on Epigenetics by Arrowsmith et al. Below is a brief description of the analysis, its visualization, and more technical details of the analysis methods.

This analysis is based on three primary metrics computed on the prior 10 years of epigenetics research publications. Each protein is analyzed to determine the degree to which it is:

• Emerging: Quantifies the degree to which epigenetics research is increasingly focusing on each protein relative to the historic levels of research focus on the protein.

• Establishment: Quantifies the degree to which epigenetics research has focused on this protein since 2001.

• Targeting: Quantifies the degree to which this proteins has been discussed in research publications in context of molecular targeting applications. This serves as a useful metric for quantifying the drugability and utility of drugging each protein within therapeutic applications.

Data Visualizations:
The two bar charts at the top of the interface represent the degree to which each protein’s respective role in epigenetics processes is supported by well-established or more recently emerging evidence. The two scores for established and emerging are ranked and put onto a scale with range of 0 to 1 so they can be interpreted as percentiles.

The scatterplots in the bottom part of the visualization represent each protein’s level of established (left) or emerging (right) evidence of epigenetics’ role on the x-axis, coupled with the degree to which each target is associated with language describing molecular targeting or therapeutic concepts in publications and grants over the past five years on the y-axis. This measure of molecular targeting provides a first-pass filter on those proteins that appear to be associated with molecular targeting research or therapeutic development.

The colors of the visualization correspond to the domain families contained within each protein. The color blue is associated with the proteins that contain multiple families of domains.

All data points can be clicked to filter and will reveal additional annotation data and links upon mouse-over.

Filter:
The filters, which are located in the right hand margin, enable users to filter out which data points are displayed within the visualizations. Each filter is described below:

• Search: This free-text search field enables one to search for partial matches on protein name, protein domain sequence (amino acid sequence only).

• Sort Order: Determines the order of the visualization of the bar graphs. Options include Name, Established or Emerging.

• Established and Emergence Sliders: Filters the data to hide the proteins with established or emergence values that fall outside of the filtered range.

• Number of Patent Refs: Filters the proteins according to the number of issued patents which reference the protein.

• Targeting: Filters the data to reveal only those within the specified range of acceptable targeting values.

• Context for Estab. and Emerg. Since the publications are dominated by research on various cancers, some users may prefer to look at the analysis in publications not explicitly focused on cancer. Therefore, this can be used to focus the analysis on non-cancer research output. This control has no impact on the targeting values assigned to each protein.

• Family: Particular protein families can be filtered out using the check boxes.

Technical Details:

Complex data mining algorithms were developed to generate this dashboard’s underlying data. Over 3.7 million published documents indexed by Medline between January 2001 and September 2012 were processed by Relay’s proprietary Relay Innovation Engine. Emerging protein targets are defined as those proteins that are increasingly associated with epigenetics-related concepts during the analyzed time period. Established protein targets are those that exhibited consistently strong associations with text-mined epigenetics-related concepts. Protein targetability is defined as proteins that are consistently referenced in association with targeted therapeutic applications – both within and outside of the epigenetics context.
This process is run via entirely automated analysis process.

Using the Dashboard:
Filters for the dashboard can be found on the right hand side of the interface. All filters will alter the visualization in dynamically. You will notice the interface updating after each filter is changed.

Below is a series of step-by-step analyses one might want to explore using this tool:

Objective 1: Identify The Most Up and Coming or Emerging Epigenetic Proteins
A) Using the ‘Emerging Filter’ in the right margin, slide the left control towards the right. This will filter out targets that are not emerging. The further you slide the control, the more emerging the remaining proteins will be.
B) The proteins can be sorted accordingly by setting the ‘Sort Order’ control to ‘Emerging’. The proteins are now sorted from most to least emerging.

Objective 2: Search For Epigenetic Proteins By Symbol, or Epigenetically Relevant Domain Sequence. For the sake of this example, assume that we would like to recall information on the ‘chromobox protein homolog 5’ otherwise known as CBX5.
A) Using the search feature in the right margin, enter either ‘chromobox protein homolog 5’ or ‘CBX5’. Likewise, a search on the protein’s amino acid domain sequence of ‘KVLDRRV’ will also recall the protein and others with a matching domain sequence.
Note that searching on ‘CBX’ or ‘chromobox protein homolog’ (the same as above but without the ‘5’) will also recall the entire family of proteins.

Objective 3: Highlight Knowledge on Proteins Containing a Particular Domain:
A) By clicking on the colored and labeled square boxes found on the left side of the interface will grey-out all irrelevant data and highlight data selected. This will enable you to focus your visual inspection on proteins in the domain family.
Note that since the data are not actually filtered, you may still need to vertically scroll through the bar charts in order to find the desired family members.

Objective 4: Use Known Proteins As Benchmarks For Setting Your Optimal Choice of Emerging or Established Filters.
Let’s assume that you would like to identify proteins that are less established than HDAC5 and more emerging than SIRT3.

A) Determine the established and emerging percentiles of the benchmark proteins HDAC5 and SIRT3 respectively.
a. HDAC5 has an established percentile of 0.918
b. SIRT3 has an emerging percentile of 0.498

B) Using the established and emerging filters in the right margin of the interface, filter out the proteins with an established percentile less than 0.918 and filter out the proteins with an emerging percentile greater than 0.498. Hint, rather than using the slides on those controls you can click on the numerical displays of the upper and lower bounds to edit them directly. This allows you to set the boundaries with precision and ease.

C) Optionally you can use the target index filter available in the right margin to further filter out proteins with target indices that are not of interest.

Objective 5: Link Out to Other Information on a Protein of Interest:
A) Often times these analyses help users find proteins that had been unfamiliar to them. In order to get more information on those proteins, simply mouse over their relevant data (either the bar chart or the scatter plot circle). After hovering briefly, a small window will appear. Within this window, the user can click on the Uniprot link in order to open a new web browser window with content from the Uniprot website.

• Monitor Industry Trends
• Identify Licensing Opportunities
• Perform Asset Scouting and Benchmarking
• Researcher and KOL Identification
• Portfolio Optimization and Pre-Clinical Development Strategy Via a Dimension-Free Data Exploration Environment.

BD Live! aggregates and visualizes structured and unstructured data from a comprehensive list of life sciences sources, including daily updates from more than 27 million data points. This unified data solution pulls together massive Big Data sources to deliver real-time, intuitive discovery for life science business development and corporate strategy professionals. Relayworks with leading pharmaceutical companies like Pfizer,Cubist Pharmaceuticals, and Stromedix (acquired by BiogenIdec).

As a platinum certified Attivio partner, TIBCO Spotfirecan connect directly to Attivio’s Active Intelligence Engine (AIE) so it can perform free text queries to search documents directly, and it connects to R for statistical modeling. A combination unavailable on any other platform for creating meaningful insights for customers.

Questions? Please email the Spotfire Team

We hope you can join us!

Register Today!

In our demo, learn how to use the Relay platform for:

• Identifying Licensing Opportunities
• Asset Scouting
• Benchmarking
• Researcher and KOL Identification
• Portfolio Optimization
• Pre-Clinical Development Strategy

Make the most of BIO by attending: 

1. Monday, June 18th: 2:30-3:30pm Business Development Professionals Meetup (Meetup Area, Booth #1211, in the BIO Exhibition)  RSVP Here

2. Breakout Session on Wednesday, June 20th: Best in Show: How to Maximize Your Company’s Selling Potential (Room 206AB)

3. On going: Tweet your Big Data and BD/L Data Questions to #BIO2012 #DataQs for a Chance to win a 16GB iPad3.  Details here

4. Wednesday, June 20th: 7:45pm – 9:30pm Attend the Gala Reception at the Museum of Fine Arts

5. On going:  Visit Relay Technology Management at Booth #2215,  Hall B to test drive the Business Development Live (BD Live!) software platform

For more information on any of these events, contact Dave Greenwald from Relay TM at dgreenwald@relaytm.com.

The rules are simple: Tweet your relevant data question to #BIO2012 #DataQs. The author of the question that gets the most retweets by the end of BIO wins a new iPad. The contest starts June 17th at 9:00 AM and will conclude at the end of BIO at June 21st at 1:o0 PM. The winner will be notified by Twitter at 1:30PM on Thursday, June 21st.

The team at Relay will use the Relay Innovation Engine software platform to answer the questions tweeted to #DataQs

For inspiration, here are some ideas for data questions:

Licensing trends
—What indication is garnering the highest upfront licensing payments in pre-clinical and phase I deals?

Venture trends
—Did Venture Capitalists put more funding into Stem Cell or RNAi companies over the past 5 years?

Evidence Based trends
—What are the top 3 targets in colorectal cancer in terms of research output and patent filings?

Key Opinion Leaders
—Who are the most translational academic researchers in the Gram negative antibacterial space?

No matter the data question, we want to hear them all! While at BIO, don’t forget to tweet your questions, tagged with the hashtags #BIO2012 #DataQs, for your chance to win a 16GB iPad3.

If you have any questions, tweet to @RelayTM

Implementation of Statistical Designs in Understanding the Effect of Formulation and Process Variables on Product Quality

Speaker: Bhavishya Mittal, Ph.D., Millennium: The Takeda Oncology Company

A formulation scientist is typically faced with numerous challenges when it comes to applying statistical design in their work. For example, during early formulation development, a mixture design approach is appropriate. However, as the formulation is locked and the process is scaled-up, a cubical design space approach is preferred. This presentation will discuss some of the approaches that have been taken at Millennium Pharmaceuticals to better understand which statistical design should be applied in various situations and how to better understand the interactive effect of formulation and process variables on product quality.

The Myth of Powder Flowability

Speaker: Tian Hao, Ph.D., Neo-Advent Technologies LLC

Powder flowability is a very important classic topic in pharmaceutical solid dosage formulations. A general review of powder flowability will be presented on the basis of recent research and development work reported in literature. The powder flowability characterization methods such as shear test and flowdex measurements will be evaluated. More importantly, a systematical investigation on the correlation of powder flowability with physical properties of powder materials, like powder particle size, electrostatic charge, and tap density, among other factors, will be addressed. Neo-Advent Technologies is currently working to develop more practical approaches for characterizing powder flowability and implementing them in optimized product development.

Focused Cancer Treatment: From Drug Delivery Systems to Programmed Nano Robots

Dr. Avi Schroeder, Department of Chemical Engineering-Koch Institute of Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA
Theranostic Nano-Medicines: Applications for Targeted Imaging and Therapy in Cancer

Dr. Arun Iyer, Department of Pharmaceutical Sciences, Northeastern University, Boston, MA

Focused Cancer Treatment: from Drug Delivery Systems to Programmed Nano Robots

Metastasis is the cause of 90% of cancer deaths. In many cases, by the time a primary tumor is detected, subsets of malignant cells have already disseminated to other locations in the body seeding the spread of the disease. Nanoparticles have many potential benefits for treating metastatic cancer, including the ability to transport complex molecular cargoes, as well as targeting to specific cell populations. The lecture will describe the development of lipid nanoparticles, loaded with drugs and small interfering RNA (siRNA), that can be remotely triggered to release their payload in tumors. The evolution of these nanoparticles into programmed nano robots, unique particles that have an internal capability of synthesizing proteins, and their promise for treating metastasis, will be addressed. Furthermore, the lecture will describe miniature electronic devices that we developed for enhancing the delivery of drugs to specific tissues.

Theranostic Nano-Medicines: Applications for Targeted Imaging and Therapy in Cancer

Cancer still remains a major cause of morbidity and mortality worldwide, with more than 10 million new cases reported every year. However, there have been significant developments in recent years in reducing the mortality rates owing to better understanding of tumor biology, novel diagnostic and therapeutics tools for early detection and treatment of cancers. Conventional treatment methods include surgical resection, radio- and chemotherapy involving cytotoxic agents, which often lacks targeting and indiscriminately kill healthy cells and tissues causing severe systemic toxicity to cancer patients. It is, therefore, desirable to develop novel therapeutics that can either passively or actively target tumor tissues selectively. Passive targeting involves exploiting the pathophysiological abnormalities of the tumor microenvironment to deliver macromolecular drugs and nanocarriers by the enhanced permeability and retention (EPR) effect. Active approaches achieve more selective tumor targeting by the use of nanocarriers coated with molecules or ligands that can bind to over-expressed receptors or antigens on the target tumor cells. Nanocarriers can also be loaded with imaging and contrast agents for visualization and early detection of tumors – a critical step in diagnosis and management of cancers. The so called ‘theranostic nanomedicines’ can be engineered with a cocktail of therapeutic drugs and genes, imaging agents, and tumor homing molecules for simultaneous real time assessment and targeted therapy of cancers. This presentation will focus on the potentials of nano-medicines utilizing active and passive tumor targeting principles and highlight the challenges and perspectives in their clinical translation.

Bios

Dr. Arun Iyer is currently an Associate Research Scientist in Prof. Mansoor Amiji’s Laboratory in the Department of Pharmaceutical Sciences at Northeastern University. He received his Ph.D. in Polymer Chemistry under the supervision of Prof. Hiroshi Maeda at Sojo University in Japan, and completed his postdoctoral training at the University of California, San Francisco (UCSF.) He has broad research interests in polymeric biomaterials for tumor drug targeting, biomedical imaging, advanced drug and gene delivery systems, and nanomedical technologies.

Dr. Avi Schroeder is a Postdoctoral Fellow in Robert Langer’s Lab at the Department of Chemical Engineering and Koch Institute for Integrative Cancer Research, the Massachusetts Institute of Technology. Avi received his PhD in Chemical Engineering from the Ben Gurion and Hebrew Universities in Israel in 2009. He is the author of 19 peer-reviewed papers and inventor on 10 patents. Among others, Avi is a recipient of the Intel Nanotechnology-, TEVA Pharmaceuticals-, and the Wolf Foundation PhD Awards.