Simulations Plus

Here is computer scientist David Gelernter’s [1] answer to the annual question “2013 : What *Should* We Be Worried About?” at the website Edge [2].

In 2005, playwright David Mamet* wrote a memo to the writers of the TV show The Unit that went viral on the internet. I have taken some liberties to adapt the memo to pharmacometricians on drug development teams. If you read the online version of the real memo, you will see that I did not have to do much editing, save for redefining the word “drama.”

Welcome to the beginning of 2013. Most of us, I bet, had a challenging 2012, certainly it was stressful, but there is so much to be grateful for and, if one is optimistic, there are many opportunities that are full of promise for the New Year.

A New York Times* online essay by Gary Gutting, a philosophy professor, contains one of the clearest explanations of the differences between inductive and deductive reasoning I have seen.

Criminologist David M. Kennedy’s (1) strategy for reducing gang violence has dramatically reduced youth homicide rates nationwide. Dubbed the “Boston Miracle,” this strategy brings together all the key actors in a neighborhood from the police and community members to gang members, drug dealers, and their mothers and grandmothers to openly discuss their issues. Boston’s youth murders were cut by two thirds after installation of the program (2).

Being the Team Leader of an R&D team might not be down at the level of some of the jobs on Mike Rowe’s Dirty Jobs on TV’s Discovery Channel, but I nominate it as the worst job in Pharma.

Carole King, a songwriter and singer who has 4 Grammy Awards, was interviewed last spring by Terry Gross on the nightly NPR program, Fresh Air.

Scientific excellence–asking the right question, then designing and conducting a valid study that answers that question and influences future research–is widely accepted as a benchmark for success in research. However, excellence of a more complicated sort is required in Pharma research. For example, excellence in pharmacometric modeling and simulation has to encompass 3 types of excellence: strategic, operational, and technical.

Elmer Sperry (1860-1930) is remembered as the father of cybernetic (feedback control) engineering. He was the author of more than 350 patents in a wide range of fields, and he developed gyro-controlled steering and fire control systems used on Allied warships during World War I and World War II. He was among the first of the independent inventors of the early 20th century to be elected to the National Academy of Sciences (1).

After writing about gap analysis for the Pharma of the Future? blog, I went in search of an example that would illustrate the problem of defining “gaps” and stumbled on a piece called Reading and Guilty Pleasure in the New York Times. The writer, Gary Gutting, describes 2 assumptions underlying the concept of a guilty pleasure: some books are objectively inferior to others, and “better” books are generally not very enjoyable. So, are “better” books actually better? Gutting says that in discussions of this sort, people will often adopt a relativist position:

I was talking with a Program Director the other day about an upcoming regulatory filing. She was rightly proud of the clinical pharmacology work that had been completed, but she was also anxious about possible holes in the package. As we talked, I thought about how gap analyses have changed over the years, particularly since modeling and simulation results have come to play a larger part in the Clinical Pharmacology Summary in NDA submissions.

Each week, the Mathematical Association of America website posts a new math-related photo that was submitted by an MAA member. The photo reposted here is a decorative Venn Diagram on a ceiling light that was featured on May 31, 2011. The photographer was Joy Hsiao of Brooklyn Technical High School. Visit the MAA Found Math gallery to view more of these fascinating photos.

Susan Cain recently wrote about the advantages and limitations of team work versus going it alone in the New York Times Sunday Review.

In a podcast called Thinking About Thinking, three eminent scientists discuss the ways humans think. All three have interesting and useful insights. I recommend this podcast to anyone responsible for managing Pharma R&D teams or for anyone looking for new ways to improve team performance, especially in knowledge-intensive research efforts.

George Steiner:

Our world is shrinking. Science is becoming inaccessible to us. Who can understand the latest innovations in genetics, astrophysics and biology? Who can explain them to the profane? Knowledge no longer communicates; writers and philosophers in our day are incapable of enabling us to understand science. At the same time, the scope of imagination in science is dazzling. How can we claim to speak of human consciousness if we overlook what is most daring and imaginative? I am concerned by what it means to be literate today. Is it possible to be literate if you do not understand non-linear equations?

Frances Fukuyama had some interesting things to say in the current issue of Foreign Affairs about the implications of globalization and technical innovation for our children’s future.*

I know, I know — you don’t want to read another doom and gloom blog. But, in a recent article in the National Review* (link is no longer available), Peter Thiel does an excellent job of linking the desperate necessity of advancements in technology and science with the broader societal crises we are now experiencing. Thiel posits that there is a mistaken, but nearly universal, background assumption about easy progress that underlies our unwillingness to tackle difficult problems.

Back in 1974, Stewart Brand’s advice was to “stay hungry, stay foolish,” as a way of bringing a beginner’s mind to new challenges. He still follows that advice, and he now says, “The phrase allows you to open your mind and explore. It means putting aside the explanations provided by social constructs and ideologies.”

Chapter 3 of 3. Need to catch up? Read the previous post in this series about scientific workflows.

In the same way that the guillotine concentrates the senses, the need to improve productivity in the pharmaceutical industry has become a life-or-death imperative. Improving productivity does not mean working harder and faster while doing the same job as before. Improving productivity lies in innovation—in the technology and processes that clever minds bring into existence. Moreover, what this innovation must accomplish is vividly clear. We must reduce the time and cost of drug development; increase the probability of successful experiments; and bring better drugs to the marketplace.