LSMP Lecture Notes - Dr. Robert Burns & Dr. Philip Rea; Life Sciences and Management Program PDF

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Dr. Robert Burns & Dr. Philip Rea; Life Sciences and Management Program...

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Lecture Notes 1.Tuesday, Aug 30th: Introduction a. Comprehensive application of science to make products in the healthcare system i. R&D side as well as commercialization side ii. All about life sciences ie.e pharma, biotech, medical devices, IT b. Translational medicine → how to make the leap from R&D side to commercialization c. Contemporary issues at hand i. High cost of innovation/stagnation in innovation ii. Willingness to pay for it? iii. Can science be a business: biotech? Can it really make it as sustainable? iv. Translation of innovation into Physician practice? 1. Maybe you have a product, gov’t wants to pay for it, ---but doc doesn’t prescribe?? Thus plug is pulled on the project a. What is the doctor doing w conventional therapies? And how does your product make it better d. Course Introduction i. The Healthcare Value Chain 1. Payers< --->ProvidersProducers a. I.e. government and employers; are insured by hospitals or health plans; providers apply it; related to distributors; producers like pharma, biotech b. Essentially an Ecosystem; they all interact with each other ii. The Twin Towers 1. ALL of the tech sectors in health care iii. Spend the money now on R&D, has a therapeutic and beneficial advantage downstream; innovation can be expensive 1. Avoiding hospitalizations is cost saving by making great drugs a. Gaining drug coverage reduces other medical spending; cost offsets 2. Substitution effect

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a. An expensive drug is at least cheaper than going to a hospital, using physicians, using facility, etc. Value Chain in BioPharma 1. Slowly converging call it biopharma to recognize that 2. What is R&D? a. Planned, creative work to discover new knowledge or develop new improved goods i. Basic research: acquiring new knowledge or understand without immediate application use ii. Applied research: Activities aimed at solving a practical problem or meeting a specific commercial objective iii. Development: Use research in a way to produce new or

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significantly improved goods/services for the market b. The Pharmaceutical Value Chain i. R:: Scientific Innovation “Invention Business” ii. D:: Demand Realization “Innovation Adoption Business” Varying Scope of Pharma Business Models 1.

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Discovery → Development → Product/Commercialization

a. Discovery consists of the basic & applied research 2. The most R&D intensive sector a. Most R&D spending is in development side to get those drugs commercialized 3. Industries do the most funding on R&D compared to fed gov’t/philanthropy R&D Investments: Risk & Return 1. I.e. Takes 2.6 billion to develop one new approved drugs; the costs of drug development have more than doubled in the past century 2. Very risky i.e. in discovery stage only 1-2% make it 3. But success is highly rewarded - margins are crazy good; most lucrative field in healthcare 4. Trends in R&D Investments a. R&D Spending Growth has tapered Types of innovation 1. Product innovation: a. Incremental, radical, revolutionary 2. Process innovation: new or greatly enhanced production or delivery method Stages of Research discovery process: 1. Target identification → target verification → lead generation → lead optimization

2. States of development: a. Pre-clinical development b. Clinical trials: Phase I, Phase II, Phase III e. Big Continuing issue: i. Product innovation & productivity of pharma ii. Efficiency of pharma continues to fall eroom’s law: “pharma develop cuts in half every 9 years” iii. It seems like we are not being productive at all since we continue to spend more funding on innovation and yet we only approve so little NMEs by FDA’s CDER annually iv. Hypothesis: Maybe in 1990 was the end of the blockbuster era? (Blockbuster=a drug with >1 mil dollars in sales) 1. PDUFA 1997 a. Prescription Drug User Fee Act b. FDA didn’t have enough manpower on hand to handle all the drug applications c. FDA said, we’ll review your drug, if you pay us. i. Drug companies gladly did, FDA hired more, so 1997 was a giant boom and outlier

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The backlog got processed that year but the year after it went back to normal Nonetheless, we are still pretty much at a flatline on this graph. So why the flatlined productivity? One of the greatest challenges is that the cost of creating drugs rises but productivity stays the same 1. Costs more and more for R&D but the output is pretty much constant and flatlined 2. Pharma’s main reason for drug prices going up (barring people who jack up prices like Martin Shereli) Pharma’s main customers are physicians and patients 1. But since 1990, pharma’s stakeholders expand ie investors, media, gov’t payers, regulators i.e. FDA

2.Thursday, Sept. 2nd: Managerial Pharmaceutics a. Perspective on Innovation i. Only true global sector: healthcare innovation i.e. pharmaceuticals, devices, suppliers 1. Healthcare is the #1 global growing industry 2. Suppliers are typically global industries cause innovation is created everywhere and they want to sell a. Most profitable segment of healthcare i. The Penn health system makes half the revenue of the university b. Many sectors now diversifying into one another’s space i. Pharma is entering biotech and biotech is entering pharma ii. Innovation is time and money iii. Innovation occurs within a multi-tiered ecosystem 1. What motivates the decisions a physician makes? 2. What motivates the decisions a patient makes? 3. We need to understand these two because we need to understand the interaction between the patient and doctor to really understand innovation b. Innovation levels i. Individual levels 1. Innovation comes from people who are polymaths (people with different disciplines under their belt) c. Management of healthcare i. Can discovery in the life sciences and those individuals who make the discoveries (eg scientists) be managed? ii. What can you take away from your Wharton management training to influence the field and alter this trend of the flatline? Should you? d. What is management? i. Getting employees to do things they shouldn't do; aka disciplining employees 1. But it’s hard to do that in the field! 2. Knowledge workers i.e. researchers crave independence 3. “Vagaries” of innovation

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a. It’s so hard to predict how to spur innovation Levels to consider management from: 1. Individual level a. This is where you must view creativity inherent from b. Polymaths & boundary spanners i. Trained to communicate interdisciplinary ie. bio/business c. Tinkering; ambidextrous d. Quasi-schizophrenics: intuition and implicit learning e. Wild Ducks & Black Sheep i. Former IBM CEO Tom Watson actively recruited “Wild Ducks” and Steve Jobs did the same with “Black Sheep” f. Serendipity (luck) & pursuit of unintentional findings g. Mihaly Csikszentmihalyi i. Said creative people have dimensions of complexity 1. But if you’re not inherently creative, what do you do? Surround yourself with others who are a. I.e. Bell Labs architecture is oriented so that once you walk out you serendipitously bump into someone of another field to talk to. 2. Group Level a. Collective creativity: brainstorming b. George Wilhelm Friedrich Hegel philosophy i. Debate among different perspectives is Hegelian dialect ii. Two ideas in mind warring against each other 3. Departmental Level a. Organic structures ie loosely structured, decentralized b. Characteris like small focused R&D Units, organizational balance 4. Firm Level a. I.e. Bell Labs i. Scientific autonomy, patience, let scientists innovate on their own ii. Technically competent management who appreciates scientific innovation 5. Interdisciplinary level a. Convergence of multi ideas

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3.Tuesday, Sept 5th: Guest Speaker John Kunios a. The “aha” moment i. Insight b. Negative correlation between percentage of solutions that are insights & percentage of errors that are “errors of commission” i. I.e. the more insightful people tend to timeout more often since they just don’t know what to say 1. The more analytic people make more mistakes in commentary since they still say stuff drawn from a wider thinking bank c. Anterior cingulate i. Becomes more active when you’re happy and helps steer positive solution paths; allows you to think broadly in scope ii. Resting states → preparatory states → sensory gating → insight 1. Insight is related to neurological reward feeling “sense of accomplishment” 2. Insight itself is subjective but from the interviews they take objective patterns to link similar ideas a. Trying to find an objective marker in the brain d. Practical implications of following principles? i. Positive mood facilitates creative insight 1. Corporate culture/environment ii. Creative insight are intrinsically rewarding iii. Insights often pop into awareness when you aren’t actively working on a problem e. Flow has nothing to do with creativity i. State of concentration ii. Link of flow and creativity is a misnomer iii. Not much empirical basis of research

4.Thursday, Sept 7th, Guest Speaker a. Translational research in genomics and personal genome sequencing

Genomic Medicine 1. Transitional single gene disorders (Genetics) 2. Analysis of whole genome (Genomics) ii. Personalized Medicine: 1. “The use of information and data from patient’s genotype to stratify disease, select a medication, and provide a therapy 2. More broadened definition: a. Is the practice of clinical decision making such that decisions maximize outcomes the patient cares most about and minimizes those that the patient fears the most, on the basis of as much knowledge of the individual's state as is available b. Personalized medicine vs precision medicine i. Clinicians practice personalized medicine (and always have) ii. Currently: intuitive medicine 1. Very reactive-based, just test medicines and look at empirical results a. “Hoping for the best” 2. Empiric ‘trial and error’ iii. Future: Precision medicine 1. Expect genomics to play a key role in this 2. Providing care that can be precisely diagnosed whose causes are understood and which can be treated with rules-based therapies that are predictable effective c. Sequencing i. Used DNA Sequencing (Sanger Method) ii. Whole Genome Shotgun sequencing method d. Comparing the two i. Traditional Sanger sequencing 1. Slow, expensive ($1-5,000 per gene) 2. Determines DNA base, highly accurate 3. Virtually used for all current genetic testing ii. Whole Genome Sequencing (WGS) 1. Fast, inexpensive (and getting cheaper; approaching $1000 per genome) 2. Assigns that the probability for a given DNA base at a certain location 3. Variable accuracy 4. Poor coverage of some regions of the genome 5. Rapidly expanding into the clinic iii. Justifications for WGS: 1. Cheaper to sequence the entire genome that doing one or two genes 2. Does prevention save money? a. Premature death saves healthcare costs (obviously) b. Avoidance of adverse events 3. The economic impact of more effective therapies a. Decrease costs i. Less waste if therapies can be targeted b. Increase costs i. Treatments for the untreatable ii. Longevity i.

e. Healthcare economics i. What is value? 1. Crudely some relationship between outcomes and cost of care 2. Patient centered outcomes include: a. Medical outcomes (treatement, prevention, safety) b. Service outcomes (number of visits, disruption of life) c. Information (research data) i. Highly valued in genetics ii. Difficult to value economically iii. Persona utility vs. control of health care costs 3. Currently the US is not getting enough value from the money that we spend on healthcare a. I.e. Japan spends ⅔ less but better health care delivery b. Literally in rural parts, it is more dependent on ZIP CODE than GENETIC CODE due to health delivery inequity ii. Newborns 1. Newborn screening: a. Combine analyte screening and genomic sequencing? iii. Genoics over the lifespan 1. Advantages a. Cost spread out voer life of care b. Avoids need to repeat testing c. Info can be used as soon as it is needed d. More precise pharmacologic therapy i. Avoid adverse events ii. Choose best tolerated mot effective therapy 2. Questions a. Storage of info b. Informational available c. Discrimination iv. Strategy 1. Basic genetic/genomic and other knowledge 2. Intelligent filter 3. Ready for prime time 4. Informatics 5. Quality outcomes f. Realizing Precision Medicine i. Mass customization 1. Problems with this in medicine a. Evidence for therapies is almost exclusely population based i. FDA drug approval requires this to determine efficacy ii. Current EHC systems do not support aggregation of relevant patient data at the point of care iii. Number of data elements surpass human cognitive capacity iv. Limited ability to collect outcomes data from real world to determine effectiveness of personalized intervention

g. GenomeFIRST i. The prompt for the clinical encounter is the DNA variant ii. Patients sign broad consent to combine EHC data and biospecimens iii. Exome sequencing on 94,000 participants iv. Define outcomes for GenomeFIRST program 1. PCP management 2. Clinical genomics (CG) management h. On the verge of a revolution in medical care of which genomics is a part

5.Tuesday, Sept 12th: Statins a. Drawing striking parallel between Fleming (penicillin) and the discovery of statins (fungal systems) b. Akiro Endo (Ph.D.) discoverer of the very first statin (mevastatin) i. A class of drugs which serve to lower blood LDL-C (low density lipoprotein cholesterol) levels and confer protection from cardiovascular disease (CVD) ii. Largely because of this work, today’s physicians have at their disposal cholesterollowering statins i.e. simvastatin, lovastatin, atorvastatin (Lipitor), etc for combating CVD c. A closer look at CVD: i. Since 1900, CVD has been the number 1 killer every year in the US ii. CVD is the #1 killer of women - a woman is 10x more likely to die from heart disease than from breast cancer d. CVD impact on health delivery systems i. CVD is highest ranked disease category for hospital charges e. Dietary cholesterol is not the killer but rather the cholesterol produced in your own body f. Atheroi. Deposits formed in fatty streaks ii. Obstruction of blood flow is very unlikely an acute event; buildup of cholesterol iii. Anthrogenic diet - high in fats/meat and high calories g. Cholesterol: what is it? i. Cholesterol is a fatty steroid made primarily in the liver of most animals and humans. ii. It is a precursor for the synthesis of steroid hormones and is a major constituent of membranes h. The framingham heart study i. High serum levels of HDL cholesterol found to reduce risk of death

6.Thursday, Sept 14th: Statins cont. a. Low density lipoprotein (LDL) Structure i. Many triglycerides (fat) ii. Covered by phospholipid monolayer b. Akira’s story of developing metastatin

7.Tuesday, Sept 19th: From Precision Medicine to Precision Prevention a. Genomics, precision medicine and public health (bigger picture of translation) i. Intersection of precision medicine and public health 1. Think beyond biodiscovery to the bigger picture; framing what you’re doing for the larger system ii. “The All of Us Cohort” (Precision Medicine Initiative @ NiH) b. The US spends the money money per capita healthcare but the results aren’t that much better. I.e. Countries spend less on healthcare & perform better than US i. “Netter Research” 1. Looks across data to see what works/doesn’t work c. Takes avg 17 yrs for most successful discovery to enter clinic d. Genomics across the lifespan i. Can screen at an early age - since you’re born with it 1. Everyone has their own genome and genetics manifests across lifespan ii. Complex disease results from gene-environment interactions (environmental risk factors i.e. infection & chemicals) 1. Also combined with epigenetics (post-genome modification) e. Tension between precision medicine and public health i. If only focus is on the genomic discovery, you lose the opportunity to make a greater difference without the greater picture f. Population Health Impact Pyramid i. Socioeconomic factors → Changing the context (making smoke-free laws, fluoridation) → long-lasting protective interventions (immunization, brief intervention) → healthcare interventions 1. Goes from largest impact to smallest impact g. Traditional Genomics Translational: Bench to Bedside i. From base pairs to diagnostics & therapeutics h. Expanding translation to public health practice i. T1: 1. Discovery → intervention a. Shows success of some clinical trials b. But currently AMA hasn’t published it; FDA not approved it i. Doctors are very unlikely to incorporate into their practice ii. T2: 1. Evidence-based Recommendations iii. T3: 1. Routine Healthcare Practice a. Take evidence from clinical trials to say this should or shouldn’t be used in practice b. Think beyond randomized clinical trials iv. (Side note): Knowledge integration cycle 1. Make clinical decisions tools based on data 2. Actively taking information from research or EHR a. Since tech is more data & electronic based

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According to research, limited translational research in genomics beyond the bedside ClinGen: Curating the Human Genome i. Take genetic variant - and decide if it’s worth pursuing 1. Is the gene associated with a disease?

a. Clinical validity 2. Is the variant causative? a. Pathogenicity 3. Is this information actionable? a. Clinical usefulness ii. Categorized into tiers for viability Tier 1 is green light 1. Ex: a. Familial Hypercholesterolemia i. Treatment gaps still present ii. But even after meds, more than half of patients did not achieve adequate LDL-C lowering 2. Commonalities: a. Autosomal dominant disorder w adult onset b. Relatively common k. Need approach a population health and multidisciplinary translational sciences (expanding the 2%) l. Introducing the ALL OF US COHORT PROGRAM i. Vision of President Obama of the Precision Medicine Initiative ii. Research is set up so 1. PI is lead, there are workers, they get research participants 2. But only annual newsletter is sent to patient a. How do we get patients more involved in research on our end? iii. Accelerate translation 1. Siloed fields iv. Program overview: 1. Accurately reflecting diversity of US; want to collect patients to form larger sample size of all diversity in US 2. Major building blocks of research program a. Biobanks 3. Sheer size = statistical power to detect rarities 4. Incr representative of diversity demographics & geography 5. Collecting wide panel of data 6. Vehicle to incr patient engagement

8.Thursday, Sept 21st: Cancer Drug Research a. Looking at the advances in genomic research & cancer research b. Cancer is prevalent like almost ¼ of people know someone w cancer i. Data in many press news shows that cancer research has not lowered death rates compared to i.e. stroke & heart disease ii. Change in genes/epigenetics affect cancer risk iii. But how much increase is due to improved screening and just recognizing cancer?

1. Sometimes screening early is pointless and leads to unnecessary treatment c. What is cancer? i. Hundreds of different related disease 1. Each person’s tumor is different from another’s tumor a. Tumor is not a bag of cancer cells, but a combination of some cancer cells and regular somatic cells. ii. Loss of homeostatic control 1. Complex series of molecular controls evolved to ensure functions like cell division, differentiation, and turnover in normal tissues a. But these controls are lost or impaired during the evolution of cancer iii. Malignancy eventual result 1. Localized disease → disseminated disease 2. By the time diagnosis is readable, the invasion has spread already iv. Cancer as a disease of altered gene function 1. Epigenetics - changes in environment affect gene function by affecting on/off by histones & methylation characteristics v. Normal cells have a low, but measurable mutation rate, caused by inherent irrors in DNA repair during cell division 1. Cancer only arises from rare combinations of mutations in speicfic genes that together change cell division, survival, motility. d. Canc...