INDEX

Abcam, 120–121

Abgent, 119–120

adaptive trial design, 213–215

Africans, 128

aging, 33

AIDS, 142–143

Akey, Joshua, 128, 129, 184–186

Albert Einstein College of Medicine, 180

Alberts, Bruce, 193–194

Alkhateeb, Ahmed, 231

Allison, David, 182–183

ALS (aka Lou Gehrig’s disease or amyotrophic lateral sclerosis), 2, 82, 155–156

ALS experimental design, 53–63

animal model as valid surrogate for human disease and, 68–69

animal studies vs. human drug trials and, 54, 55–57, 58–59

drug development, 62

drug testing costs, 56–57

funding, 53–54, 57, 61–62

grant application guidelines, 60–62

reproducibility, 59–60, 62

ALS TDI. See ALS Therapy Development Institute

ALS Therapy Development Institute (ALS TDI), 55–56, 61–63, 68

Alzheimer’s disease, 1, 2, 11, 42, 82, 83

American Society for Cell Biology (ASCB), 16

American Society for Reproductive Medicine, 105

American Statistical Association, 138

American Type Culture Collection (ATCC), 98, 103, 106, 107

Amgen, 7–9, 16, 26, 39, 40, 116

amyotrophic lateral sclerosis. See ALS

anatomic pathologists, 200–201. See also pathologists

Andersen, Olaf, 45, 178

anesthesia, 198

animal model, as valid surrogate for human disease, 68–69

animal-research guidelines, 233

animal studies, 64–65

animals used in, 71, 72

bias in, 75–76

chips in place of, 85–87

deadly consequences of, 71–72

drug development and, 91

drug testing and reliance on mice in, 74–79

drug-toxicity tests and, 72–73

drugs for hepatitis B and, 71–72

elimination of variables and, 79–80

failure rates, 81

human disease and, 73, 76

vs. human drug trials, 54, 55–57, 58–59, 71–72, 77

induced pluripotent stem (iPS) cells in place of, 83–84

laboratory vs. wild mice in, 78–79

mouse lab issues and, 79–82

for neurological disease as irrelevant, 82–83

number of animals used in, 73–74

replacements for, 82–87

shortcomings, 71–74

technology and, 83–87, 87–88

antibody testing, 232

gene-editing technology and, 120–121

improving the quality of, 118–122

index array slides and, 119

irisin for weight loss and, 116–118

melanoma and, 112–113

misleading results from, 112–118

reproducibility and, 122

anticancer drugs, 51–52, 89, 109, 199

Aristotle, 30

Arizona State University, 21, 199, 212–213, 235

Armanios, Mary, 35–36

ARRIVE guidelines, 233

Artandi, Steven, 35, 36

arthritis, 142

Artman, Stan, 112–114

ASCB. See American Society for Cell Biology

Asia, 178

Asians, 127–130, 184–186

aspirin, 73

asthma, 132

AstraZeneca, 75

ATCC, 107

Australia, 97, 214

autism, 84

Bacon, Francis, 30–31

bacterial genes, 152

bad science, natural selection of, 188

badges, 232

Baggerly, Keith, 123–125, 126–127, 129–130

Barker, Anna, 21–22, 201–203, 213–215

basic research, 11, 17

batch effect, 125, 126–130, 184–185

cancer research and, 201

Bayer, 9–10, 11

study of reproducibility failures, 59–60

Begley, C. Glenn, 7–10, 12–13, 14, 25–27, 39, 40, 60, 116, 157–158, 220, 227–228

Belgium, 106

bias

in animal studies, 75–76

in reproducibility, 15, 40–44

Biden, Beau, 19

Biden, Joe, 19

big data, 130–133, 196. See also data analysis; data sharing

biologicals, 91

biology, 31, 34–35, 36, 38, 130

Darwin and, 169–170

as quantitative, 203

from small studies to big data and, 196

biomarker validation, 210–213, 211–212

costs, 212

reproducibility and, 211

biomedical research

acknowledgment of problems in, 3–4

analysis (see data analysis)

animal-research guidelines, 233

ARRIVE guidelines, 233

competition for postdoctoral academic, 173–174

confirmatory vs. exploratory, 140–141, 145, 147

costs, 2, 219

data-driven medicine and, 218–221

drugs and (see drugs/pharmaceuticals)

federal support for, 3

fraudulent, 7

funding (see research funding)

incentives to improve, 224–235

incentives to improve, and badges, 232

meta-research and, 216, 217–218

method shortcuts and, 1, 3, 4

methodology, 150, 165

methodology sharing, 150

needed improvement in, 223–224

non-attachment and, 32

pharmaceutical companies, and incentives to improve, 227–228

poor quality of, 227–228

problems and solutions, 192–196, 216, 217–236

publishing guidelines and checklists, 233

quality over quantity, 235, 236

raising awareness and, 233

raising standards and, 233–234

reasons for slowness of, 1

research reproducibility (see reproducibility)

self-correction, 143

to speed up and to slow down, 235

training for career in, 28

Transparency and Openness Promotion (TOP) guidelines, 233

unforced and unnecessary errors in, 3

as weak and errant, 7

See also breast cancer research; cancer research; fertility research; genetic research; genomics research; glioblastoma/brain cancer research; meta-research

biomedical scientists

challenges facing, 29–30

competition among, 170–179, 194 (see also scientific misconduct)

fooling oneself and, 29–30, 31

promotions and tenure and, 12, 174, 224–226, 233

resistance to disruptive ideas by, 78

rewards and penalties and, 12

set up for failure, 12

solutions to structural and funding problems and, 192–196

sources of bias and error among, 15

biophysicists, 57–58

bioRxiv.org, 230

biostatisticians, 4, 126, 142–143, 185–186. See also statistical significance; statistics

Bissell, Mina, 46

Blackburn, Elizabeth, 33–35

blood infections, 78

blood-pressure drugs, 17–18

blunt instruments, 43–44

Boldt, Joachim, 181

bone marrow stem cells

transdifferentiation and, 23–25

See also stem cells

Boos, Dennis, 136–137

Bourne, Henry, 190, 194–196

brain cell research, 84

brain damage, stroke related, 74–75, 76

brain tumor/cancer research. See glioblastoma/brain cancer research

breast cancer research, 219, 222

adaptive trial design and, 214–215

breast cancer test and, 199

cell lines and, contamination and misidentification of, 99–104

genetic profiling of, 212

tissue collection and analysis and, 199–200

breast tissue/breast-reduction surgery, 45–47

Bristol, Muriel, 134–135

Broad Institute, Cambridge, MA, 62, 204–205, 207

Brown, Pat, 100

Bugge, Thomas, 48–49

burns, 77–78

Caileau, Relda, 99, 102

Califf, Robert, 226

Campbell, Bill, 121

cancer, 1, 11, 33, 109

cancer-causing agents, 73

drug development, 203–210

metastatic, 2, 47–49, 100, 114

See also specific cancers

Cancer Genome Atlas, The (TCGA), 202

cancer immunotherapy, 51–52

cancer research, 7–10, 21–22, 89, 195

acknowledgment of inability to reproduce and, 10

adaptive trial design, 213–215

antibody testing and, 112–113

batch effect and, 201

blood sample collection, 201

cell lines, 204–205, 207–209

cell lines and, contamination and misidentification of, 94–96, 99–104, 106–109

chemotherapy and, 8

clinical trial failure rate, 21

costs, 22, 210

G-CSF and, 8

genomics research and, 202–203

problems, 22

reproducibility in, 8–10, 156–164

standard operating procedures and, 202–203

tissue collection and, 197–203

See also breast cancer research; glioblastoma/brain cancer research; other specific cancers

Capes-Davis, Amanda, 97–99, 99, 102, 111

Carl XVI Gustaf of Sweden, 177

Casadevall, Arturo, 17–18, 164, 165–167, 169–170, 182, 236

Catholic University of America, 96

Caucasians, 127–130, 184–186

Cech, Tom, 36–38, 171

Cell, 175, 176–179

cell banks, 97, 98, 103, 106, 107, 110

cell-fingerprinting technology, 98

cell lines, 130, 203, 232, 233

antibody tests and, 122

cancer, 94–96, 99–104, 106–109, 204–205, 207–209

cell lines, contamination and misidentification of, 93–122

authentication and, 109, 122

avoidance of misidentification, 109–111

breast cancer research and, 99–104

cancer research and, 94–96, 99–104, 106–109

cell-fingerprinting technology and, 98

cell line sharing and, 110

fertility research and, 93–94, 104–106

glioblastoma/brain cancer research and, 106–107

NIH and, 96–97, 108–109

SNP analysis and, 111

testing systems and, 110–111

cells, 10–11

brain, 84

induced pluripotent stem (iPS), 83–84

See also stem cells

Center for Open Science, Charlottesville, VA, 146, 157, 232

Centers for Disease Control and Prevention, 19

Chavalarias, David, 41

chemistry, 38

chemotherapy, 8

Cheung, Vivian, 127–128, 184–186

Children’s National Medical Center, Washington, DC, 44, 64

China, 133, 178, 214

chips, in place of animal studies, 85–87

cholesterol-lowering drugs, 72

Cleveland Clinic Foundation, 93, 104, 105–106

clinical pathologists, 200. See also pathologists

clinical research, 222–223

ClinicalTrials.gov, 147

coffee, 73

Cold Spring Harbor Laboratory, Long Island, 170

Collins, Francis, 16, 59–60, 151, 152–153

colon cancer, 197–198, 204

commercial motivation, 142

“Common Genetic Variants Account for Differences in Gene Expression Among Ethnic Groups” (Spielman and Cheung), 128

competition

among biomedical scientists, 170–179, 194 (see also scientific misconduct)

federal grants and, 174, 176

high-impact journal publications and, 174–179

postdoctoral academic research and, 173–174

promotion and tenure and, 174

telomerase discovery and, 170–172

Compton, Carolyn, 197–202

confirmatory research

vs. exploratory research, 140–141, 145, 147

A Conspiracy of Cells (Gold), 95

coronary artery disease, 132

Correlogic Systems, 125

Crick, Francis, 33

CRISPR, 120–121

Cure Duchenne, 65

Curtin, Daniel, 20

Curtin, Kevin, 20

Curtin, Lester “Randy,” 19–20

Curtin, Sally, 19–20

Dana-Farber Cancer Institute, Boston, 46, 205, 207

Darwin, Charles, 169–170

data analysis

batch effect and, 125, 126–130

big data and, 130–133, 196

commercial motivation and, 142

disclosure and openness and, 143

exploratory vs. confirmatory research and, 140–141

HARKing and, 140–142

p-hacking and, 139–140

p-value and, 126, 134–138, 139–141

problems, 125–143

reproducibility and, 130

statistical significance and, 133–138, 139

data-driven medicine, 218–221

data sharing, 150–156

reproducibility and, 150

transparency and, 150, 152

Davis, Mark, 49–52

Davis, Ron, 77–78

Defense Advanced Research Projects Agency, 84

depression, 132

Desai, Nina, 93–94, 104–106

dexpramipexole (“dex”), 55

diabetes, 90

diet drugs, 89

digital data

genomics research and, 203

direct observation, 31–33

disease advocacy organizations, 63

DNA. See under genetic research

DNA sequencing. See under genetic research

Down syndrome, 84

drug development, 89–91

ALS experimental design and, 62

animal studies and, 91

biologicals and, 91

biomarker validation and, 210–213

cancer and genome data collection, 203–210

chance and, 90

halt in, due to expense, 18

off-target effects and, 91

drug testing, 64–67

costs and ALS experimental design, 56–57

reliance on mice in, 74–79

drug-toxicity tests, 72–73

drug trials, 19–20, 21–22, 223

vs. animal studies, 54, 55–57, 58–59, 71–72, 77

drug/pharmaceutical companies

vs. academia and retaining jobs, and reproducibility, 212

anticancer drugs and, 51–52

file drawer effect and, 147–148

incentives to improve biomedical research and, 227–228

reliance on biomedical research by, 8, 13

drugs/pharmaceuticals

anti-arthritis, 142

anticancer, 51–52, 89, 109, 199

antisepsis, 77–78

approval rate of new, 18

blood-pressure, 17–18

for brain damage caused by stroke, 74–75, 76

cholesterol-lowering, 72

diet, 89

FDA approval and, 142–143

halt in development due to expense of, 18

hepatitis B, 71–72

HIV, 142–143

ovarian cancer blood test, 123–125, 127

pain, 76–77

progress in mid-1990s, 18

serious injury, 77–78

testing failures of, 17

type 2 diabetes, 90

worsening state of development of, 18

Duchenne muscular dystrophy

TACT and, 65

Duchenne muscular dystrophy experimental design, 63–67

See also muscular dystrophy; muscular dystrophy experimental design, 63

Duke University, 116

education. See scientific education

Einstein, Albert, 192

Eisen, Michael, 230

eLife, 158, 159, 161, 178

Ellis, Lee, 10, 11, 60

Emory University, 104

Emulate, 84–87

Erickson, Harold, 116–118

Errington, Tim, 157, 158, 160–162

estrogen, 219, 222

Europe, 153, 224

European Commission, 64

European Union, 67

evolution, theory of, 169–170

experimental design, 165. See also ALS experimental design; muscular dystrophy experimental design

experimental science, 29

exploratory research

vs. confirmatory research, 140–141, 145, 147

Faculty of 1000, 230

Failure: Why Science Is So Successful (Firestein), 38–39

Fanelli, Daniele, 186, 229

Fang, Ferric, 182

FDA. See Food and Drug Administration

federal registration system, 147–150

fertility research

cell lines and, contamination and misidentification of, 93–94, 104–106

fetal bovine serum, 45

Feynman, Richard, 29

fialuridine (FIAU), 71–72

FIAU. See fialuridine

fibronectin, 44–45

file drawer effect, 147–148

Firestein Stuart, 38–39, 40

Fisher, Ronald “R. A.,” 134–135

Fisher’s Exact Test, 134–135

Food and Drug Administration (FDA), 16–17, 66, 87, 105, 160, 211, 226

AIDS and HIV and, 142–143

breast cancer test and, 199

laboratory practice guidelines of, 227

new-drug approval by, 142–143

ovarian cancer blood test and, 123, 125

Food and Drug Administration Modernization Act, 147

fooling oneself

reproducibility and, 29–30, 31, 34, 40–44

fraud

scientific misconduct and, 179–186

Freedman, Leonard, 13–14, 126

Freshney, R. Ian, 97–98

Fujii, Yoshitaka, 181

funding. See research funding

“Future of Research” meetings, 193

G-CSF, 8

Galileo, 30

Garner, Joseph, 79–82

Garraway, Levi, 206–208, 210

GBM Agile, 214

gene-editing technology, 120–121

Genetech, 110–114, 207, 208, 210

genetic research, 127–130, 184–186

DNA, 33–34, 127–128, 152, 155–156

DNA sequencing technology, 88, 202, 203

genetics, 131, 170

genomics, 131

genomics research, 130–133, 151–154, 156

cancer and, 202–203

data and, 152–153, 203–210

digital data and, 203

sequencing and, 88, 202, 203

Georgia State University, 190

Germany, 116–117, 181

Gilead Pharmaceuticals, 143

GIP. See good institutional practice

Gleevec, 89

glioblastoma/brain cancer research

adaptive trial design and, 213–215

cell lines and, contamination and misidentification of, 106–107

clinical trial failures, 19–20, 21–22

personal story of clinical trials and, 19–20

See also cancer; cancer research

Global Biological Standards Institute, 13–14

Gold, Michael, 95

Goldacre, Ben, 148

good institutional practice (GIP), 228

Goodman, Steven, 31–32, 137, 217–219, 221, 222–224, 229–230

Gottesman, Michael, 103, 108–109

grants. See research grants

Great Britain, 120, 230

Greenland, Sander, 221

Greider, Carol, 33–36, 175

Haibe-Kains, Benjamin, 205–207

Hall, Richard, 192

HARKing (hypothesizing, post-result), 140–142, 145–150. See also hypotheses

Hartung, Thomas, 72–73, 84

Harvard Medical School, 204, 208, 231

Harvard University, 116, 117, 193, 198

Hawking, Stephen, 54

HealthPartners Institute, Minnesota, 186

heart attacks, 142

heart disease, 132, 219, 222

Henderson, Richard, 192

hepatitis B, 71–72

Herceptin, 199

Hesterlee, Sharon, 66

HHMI. See Howard Hughes Medical Institute

Hicks, David, 199

high blood pressure, 132

Hines, Curt, 45–47

Hinojosa, Chris, 86–87

Hippocrates, 196

HIV, 71, 142–143, 192, 210

HIV/AIDS, 18

Hoffman, Eric, 44, 63–65

hormone replacement therapy, 219, 222

Howard Hughes Medical Institute (HHMI), 24, 37, 49, 158, 183

human cells

biomedical research and, 10–11

human disease

animal model as valid surrogate for, 68–69

animal studies and, 73, 76

human drug trials, 19–20, 21–22, 223

vs. animal studies, 54, 55–57, 58–59, 71–72, 77

Human Genome Project, 153

hypotheses, 232

Darwin and, 169–170

federal registration system and, 147–150

post-result (see HARKing)

hysterectomies, 219

Ice Bucket Challenge of 2014, 53–54

images, misleading, 191–192

The Immortal Life of Henrietta Lacks (Skloot), 94

immune system checkpoint inhibitors, 51–52

immunology, 50–52

index array slides, 119

induced pluripotent stem (iPS) cells, 83–84

inflammation, 77–78

influenza genomes, 154

injuries, 77–78

Institute for Genomic Research, The (TIGR),151–152

Institute of Medicine, 72

interferons, 51

International Cell Line Authentication Committee, 99

The Invention of Science (Wootton), 30

investors, 65

Ioannidis, John, 11, 41, 132–133, 203, 218–222, 224

irisin

weight loss and, 116–118

Irwin, Veronica, 148–149

Japan, 72, 179, 181

Johns Hopkins, 127, 221, 236

Johns Hopkins Bloomberg School of Public Health, 17–18, 164

Johns Hopkins Hospital, 94

Johns Hopkins University, 72, 77, 153, 175, 182, 217, 227, 228

Johns Hopkins University School of Medicine, 35

Johnson, Valen, 137–138

Journal of Cell Biology, 47–48

Journal of Proteome Research, 213

journal publications

failure rate in, 220–222

false findings in, 217–222

false-positive results in, 220

guidelines, 233

high-impact, and competition, 174–179

high-impact, and scientific misconduct, 190–191, 193

incentives to improve, and badges/openness badges, 232

promotion and tenure issues and, 224–226 (see also under biomedical scientists)

reproducibility and, 177–178

research comment sites and, 230

retractions and, 229

scientific misconduct and, 179–186

self-retractions and, 229

journal publishers

efforts to improve reproducibility and, 228–233

Kaplan, Robert, 148–149

Kennedy, Ted, 19

Kiermer, Veronique, 172, 176–177, 178–179

Kimmelman, Jonathan, 234–235

Kirschner, Marc, 193–194

Knoepfler, Paul, 230

Korch, Christopher, 94, 99, 102–105

Korea, 178

Kunkel, Louis, 63

La Barbera, Andrew, 105

LaBaer, Josh, 212–213

laboratory practice guidelines, 227

Lancet, 124, 125

Landis, Story, 58–59

Law, Peter, 63

Lawrence Berkeley National Laboratory, 46, 192

Leek, Jeff, 128, 129, 184–186, 221

leptin, 73

leukemia, 204

Levner, Daniel, 86–87

life expectancy, 2

Lingner, Joachim, 171

lipidomics, 131

literature. See scientific literature

Lorsch, Jon, 165

Lou Gehrig’s disease. See ALS

Lyell, Charles, 170

Macleod, Malcolm, 3, 15, 74–76, 81–82

Maddox, John, 231

Madsen, Daniel, 48

manufacturing equipment, high-tech, 85

Marcus, Adam, 180–181

Martinez, Kristina, 172–175, 193

Martinson, Brian, 186–189, 233–234

Masopust, David, 78–79

mass spectrometer, 124

Massachusetts General Hospital, 204, 205, 207

Massachusetts Institute of Technology (MIT), 10, 62, 159, 181

Max Planck Institute for Evolutionary Anthropology, 188

McElreath, Richard, 188

McGill University, Montreal, 234

McNutt, Marcia, 231–232

MD Anderson Cancer Center, Houston, 10, 15, 123

MD Anderson Hospital and Tumor Institute, 99

medical progress

vs. technological progress, 88

medical research. See biomedical research

Medical Research Council Laboratory of Molecular Biology, Cambridge, UK, 192

melanoma, 112–113

Memorial Sloan Kettering Cancer Center, NYC, 201

Merck, 142, 228

Meta-Research Innovation Center at Stanford (METRICS), 216, 217–218, 229

meta-research (research on research), 216, 217–218, 229

metabolomics, 131

metastatic cancer, 2, 47–49, 100, 114

metformin, 90

METRICS. See Meta-Research Innovation Center at Stanford

microarray chips, 128–129, 184

microscopy, 88

Miedema, Frank, 225–226

Miller, Debra, 65–66

MIT. See Massachusetts Institute of Technology

Moore’s law, 18

Morrison, Sean, 24–25, 183

Morton, Don, 102

Mountzouris, John, 119–120

Murphy, Keri, 54

Murphy, Tom, 53–55, 56, 155–156

muscular dystrophy, 43–44

muscular dystrophy experimental design, 63–67

animal studies and, 64–65

drug testing and, 64–67

funding, 64

investors and, 65

standard operating procedures, 64

See also Duchenne muscular dystrophy; Duchenne muscular dystrophy experimental design

myeloma, 109

Nagaraju, Kanneboyina (“Raju”), 64–65

Nardone, Roland, 96–97, 102, 109

National Academy of Sciences, 136, 193

National Cancer Institute (NCI), 21–22, 95, 103, 193, 201

National Center for Health Statistics, 19

National Heart, Lung and Blood Institute, 148

National Institute of General Medical Sciences, NIH, 165

National Institute of Neurological Disorders and Stroke (NINDS), 57, 58

National Institutes of Health (NIH), 16, 40, 42, 47–48, 59, 60, 61, 66, 148, 180, 191, 194–195, 227

acknowledgment of problems in medical research and, 4

ALS research funding by, 57

brain cell research and, 84

cancer research, 19–20, 21

cell line contamination and misidenitification and, 96–97, 108–109

competition for postdoctoral academic research positions and, 173

federal registration system and, 147

funding of, 2

genomics research and, 154

grants, 62, 64, 115, 189, 190

hepatitis B drugs and, 71

ovarian cancer blood test and, 123

personalized medicine and precision medicine and, 196

publication guidelines and, 233

research comment sites, 230

scientific education and, 165

Nationwide Children’s Hospital, Columbus, Ohio, 43–44

natural philosophers, 30

natural selection of bad science, 188

Nature, 10, 16, 27, 60, 87, 97, 151, 152, 153, 175, 176–179, 205, 231, 233

Nature Genetics, 128, 129

Nature Reviews Genetics, 129

NCI. See National Cancer Institute

Nelson-Rees, Walter, 95, 96, 98, 99

neurological diseases, 2–3, 57–58, 82–83. See also specific neurological diseases

Neve, Richard, 110–111

New York Times, 125, 146

NIH. See National Institutes of Health

NINDS. See National Institute of Neurological Disorders and Stroke

NK-1 antagonists, 76

non-attachment, 32

North Carolina State University, 136

Norway, 106, 153

Nosek, Brian, 145–147, 149–150, 156–157, 161–163, 224–225, 232–233, 233–234

Novaric drug company, 204–205

NXY-059, 75

Obama, Barack, 196

obesity, 73, 132

Office of Research Integrity, 179–180

Ohio State University, 93

“-omics,” 131–132

oncologists, 199–200, 209

Open Science Framework, 146, 147, 149, 150

Oransky, Ivan, 180–181, 182

organ transplants, 18

artificial organs and, 85–87

organization, 146

organoids, 84

osteoarthritis, 1, 211–212

osteoporosis, 132

OvaCheck blood test, 125, 127

ovarian cancer blood test, 123–125, 127

ovarian cell lines, 209

p-hacking, 139–140

p-value, 126, 134–138, 139–141

pain studies, 76–77

Parent Project Muscular Dystrophy, 66

pathologists, 197–203

cancer research and, 202–203

clinical and anatomic, 200–201

standard operating procedures and, 202–203

Perrin, Steve, 56–57, 61–63

personalized medicine, 196

Petsko, Gregory, 42, 82–84, 176, 192–193

pharmaceutical companies. See drug/pharmaceutical companies

pharmaceuticals. See drugs/pharmaceuticals

Porter, John, 66–67

precision medicine

biomarker validation, 210–213

challenges, 196, 197–216

correlation of snippets of DNA, proteins, and other molecules with disease diagnosis or prognosis and, 198

creating new incentives and, 215–216

drug development and, 203–210

paradox of, 215

reengineering the culture and, 215–216

tissue collection and, 197–203

understanding perverse incentives and, 215

Preclinical Reproducibility and Robustness website channel, 230

preclinical research, 11

untrustworthiness of, 14

Price, Derek de Solla, 235

Princeton University, 193

progestin, 219, 222

proteomics, 131

Psychological Science, 232

psychologists, 146

psychology, 223

“Psychology’s Fears Confirmed: Rechecked Studies Don’t Hold Up,” 146

Public Library of Science (PLOS) journals, 172

publishing guidelines and checklists, 233

Pubmed Commons, 230

PubMed database, 184

PubPeer, 230

Quackenbush, John, 205–207

reagents, sharing of, 150

Reports of the Society for Experiments, 30

reproducibility, 8–18, 25–28, 29–33, 92, 177–178, 179, 217, 218, 221, 222, 228–236

academia vs. pharmaceutical companies and retaining jobs and, 212

ALS experimental design and, 59–60, 62

antibody testing and, 122

Bayer study of, 59–60

bias in, 15, 40–44

biomarker validation and, 211

blinding in, 42

cancer research and, 156–164

criticism and funding of, 37

data analysis and, 130

data sharing and, 150

direct observation and, 31–33

drug companies’ reliance on, 8, 13

of facts, 30–31

failure rates, 13, 15–16

false leads and, 37–38

fickleness of, 44–49

flawed preclinical research and, 11

flimsy study design and analysis and, 11

fooling oneself and, 29–30, 31, 34, 40–44

human cells and, 10–11

illustration of thought experiment and, 31

vs. interpretation and understanding of the mechanism, 36

journal publishers’ efforts to improve, 228–233

learning from failures in, 38–40

measurement of rigor in, 25

misleading results in laboratory research and, 11

nutrients as variable biological material and, 45

organization and, 146

poorly spent funds and, 40

preventable errors in, 40

problems and solutions, 133, 232–233

questions for researchers, 27–28

scientific disagreements in, 49–52

scientific education and, 164–167

scientific error in, 15

scientific method and, 25, 30–31

scientists’ slowness to recognize problems of, 38–40

secrecy agreements and, 26–27

self-correcting mechanisms and, 37, 39, 40

slowdown in progress and, 11, 17–18

statistical significance and, 146–147

status and perceived expertise and, 50

technical steps to improve, 232–233

telomerase and, 33–37

transparency and, 143, 145–147, 149

vested interests in, 50

Reproducibility Project: Cancer Biology, 156–163

Rescuing Biomedical Research, 194

“Rescuing US Biomedical Research from Its Systemic Flaws” (Alberts, Kirschner, Tilghman, and Varmus), 193

research funding, 226–227

ALS experimental design, 53–54, 57, 61–62

congressional, 123, 189, 195

muscular dystrophy experimental design, 64

NIH, 2, 57

problems and solutions, 192–196

reproducibility, 37, 40

scientific misconduct and, 188–190

state, for universities, 189–190

research grants

application guidelines, 60–61, 61–62

competition and, 174, 176

NIH, 63, 64, 115, 189, 190

research on research. See meta-research

research reproducibility. See reproducibility

Retraction Watch, 180–181

retractions, 229

rheumatology, 211

“rigor mortis,” 3

RIKEN, 179

Rimm, David, 114–116, 118–119, 121

RNA, 38, 170

Rosenblatt, Michael, 228

Ross, Doug, 100–102

Rowan University School of Osteopathic Medicine, 180

Salzberg, Steven, 151–152, 153–155, 163

Sarewitz, Daniel, 235–236

Scannell, Jack, 18, 88–91

Schekman, Randy, 158, 161, 177–178

schizophrenia, 132, 204

Schwartz, Martin, 32

science

judgments and truth regarding, 4–5

Science, 152, 175, 176–179, 229–230, 231

Science Exchange, 156, 157, 158

scientific discovery

power of suggestion and, 24–25

problems with, 22–25

scientific education, 164–167

experimental design and, 165

research methodology and, 165

switching fields and, 166

scientific literature

retractions in, 180–186

See also journal publications

scientific method, 1, 3, 4

reproducibility and, 25, 30–31

scientific misconduct

admission of mistakes and, 183

batch effect and, 184–185

fraud and, 179–186

funding and, 188–190

high-impact journal publications and, 190–191, 193

misleading images and, 191–192

natural selection of bad science and, 188

punishment for, 180

questionable practices vs. serious misconduct and, 186–193

retractions in scientific literature and, 180–186

unfair treatment leading to, 187–188

Scott, Sean, 55–56

self-correction, 143

self-retractions, 229

sepsis, 77–78

Settleman, Jeffrey, 204

Shatsky, Maxim, 192

Shelby, Richard, 59–60

Silberberg, Shai, 57–58

Simonsohn, Uri, 139–140, 142

single-particle electron microscopy, 191–192

“Six Red Flags for Suspect Work” (Begley), 27

Skloot, Rebecca, 94

Slusher, Barbara, 77, 227–228

Smaldino, Paul, 188

SNP analysis, 111

social media, 230

SOD-1, 68

Solache, Alejandra, 121

Sorger, Peter, 208–210

Spiegelman, Bruce, 116, 117–118

Spielman, Richard, 127–128, 184–186

St. Johns Laboratory, London, 119

standard operating procedures, 64

cancer research and, 202–203

Stanford University, 23, 31–32, 35, 36, 49, 77, 79, 100, 101, 132, 137, 186, 217, 224, 225, 231, 232, 234

states, financial support for universities from, 189–190

statins, 72

statistical significance, 146–147

data analysis and, 133–138, 139

See also biostatisticians; statistics

statistics, 13, 126, 134, 138, 141. See also biostatisticians; statistical significance

stem cells, 23–25, 86, 109, 179. See also cells; cell lines

Stephan, Paula, 190

stroke, 1

brain damage caused by, 74–75, 76

tPA and, 15

supplements, 73

Sweden, 107, 153, 177

switching fields, 166

Tabak, Lawrence, 16, 60

TACT. See TREAT-NMD Advisory Committee for Therapeutics

technological progress

vs. medical progress, 88

technology

animal studies and, 83–87, 87–88

telomerase, 33–37, 49, 170–172

Tempst, Paul, 201

TERT (component of telomerase enzyme), 35–37, 171

tetrahymena, 33–34, 91

Texas A&M University, 137

Texas sharpshooter fallacy, 140

Thomson Reuters, 178

Tilghman, Shirley, 193–194

tissue collection

cancer research and, 197–203

collecting starting materials correctly and, 201–202

TODAY show, 123

TOP guidelines. See Transparency and Openness Promotion guidelines

Torsvik, Anja, 107

tPA, 15, 74

transcriptomics, 131

transdifferentiation, 23–25

transparency, 143, 145–147, 149, 156–157, 163, 164

data sharing and, 150, 152

Transparency and Openness Promotion (TOP) guidelines, 233

trauma, 77–78

TREAT-NMD Advisory Committee for Therapeutics (TACT), 67

Truvada, 142–143

type 2 diabetes, 90

United Kingdom, 75–76, 148

universities, state financial support for, 189–190

University Medical Center, Utrecht, Holland, 190, 225

University of Alabama, Birmingham, 182

University of Bergen, Norway, 107

University of California, Berkeley, 158, 177, 230

University of California, Davis, 230

University of California, Merced, 188

University of California, San Francisco, 130, 189–190, 195

University of Chicago, 174

University of Colorado, 170

University of Colorado, Boulder, 36, 150

University of Colorado School of Medicine, 94

University of Edinburgh, 3, 74, 88

University of Minnesota, 78

University of North Carolina, Greensboro, 173

University of Pennsylvania, 127, 128, 139

University of Rochester, 199

University of Texas Southwestern Medical Center, 24, 183

University of Virginia, 145, 225

University of Washington, 128–129, 182

US Congress, 59, 161

biomedical research funding and, 123, 195

funding of NIH, 189

US Department of Defense, 64, 226

Varmus, Harold, 193–194

Velcade, 109

Venter, J. Craig, 152

Vinkers, Christiaan, 190–191

Vioxx, 142

vitamin E, 219–220

Wagers, Amy, 23–24

Wall Street Journal, 59

Wallace, Alfred Russel, 170

Watson, James, 32–33

weight loss, 89

irisin and, 116–118

Weill Cornell Medical College, 42, 45, 82, 176, 178

Weinberg, Robert, 10, 159–160, 161, 181–182

Weissman, Irving, 23

Wellcome Trust Sanger Institute, England, 204

Whitehead Institute, MIT, 62

“Why Most Published Research Findings Are False” (Ioannidis), 11, 220

Winey, Mark, 150

Woodcock, Janet, 16–17, 211–212

Wootton, David, 30

Wyss Institute, Harvard, 84

Yale University, 32, 114

Yamada, Ken, 42, 44–45, 191–192

Yamamoto, Keith, 130

Ying Su, 46–47