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Table 3 The composition of fundraising activities

From: Biopharma innovation trends during COVID-19 and beyond: an evidence from global partnerships and fundraising activities, 2011-2022

  

Average yearly amount - in US$ 100 million dollars (%)a

  

2011-2017

2018-2019 (base group)

2020-2021

2022

All Fundraising Deals (N=32,250)

Avg yearly amount: 767

Avg yearly amount: 1145

Avg yearly amount: 2615

Avg yearly amount: 1617

Deal Subtypeb

Stage of the financing cycle for the target company

          

     Early stage

Conceptualization stage with products not fully developed

42

5%

100

9%

181

7%

***

159

10%

***

     Later stage

The product is fully developed, tested, and ready to be launched

73

10%

137

12%

335

13%

***

215

13%

***

     Private equity

Acquired by a private equity firm

157

20%

183

16%

449

17%

***

186

11%

***

     IPO

Initial public offering

119

15%

116

10%

426

16%

***

104

6%

***

     Other equity offerings

Private investment in public equity or secondary offerings

376

49%

609

53%

1,224

47%

***

952

59%

***

Regionb

The geographical region where the deal took place

          

     Asia-Pacific

-

186

24%

210

18%

578

22%

***

289

18%

***

     Europe

-

155

20%

214

19%

514

20%

***

165

10%

***

     North America

-

402

52%

708

62%

1,489

57%

***

1,150

71%

***

     Others

-

23

3%

14

1%

33

1%

***

11

1%

***

All Fundraising Deals w/ Available Drug Attributes (N=17,044)

Avg yearly amount: 349

Avg yearly amount: 653

Avg yearly amount: 1466

Avg yearly amount: 673

Development Phaseb

The development stage of the least advanced drug/drug candidate in the portfolio of the target company

          

     Discovery

Identification and optimization of a substance for therapeutic use

72

21%

223

34%

684

47%

***

334

50%

***

     Preclinical

Testing of a drug in nonhuman animals or in vitro studies for a candidate drug

113

32%

261

40%

439

30%

***

196

29%

***

     Clinical

Testing of a drug in humans to determine health outcomes

99

28%

127

19%

271

19%

***

131

19%

***

     FDA reviewed/Marketed

FDA-reviewed or marketed drugs

65

19%

42

6%

72

5%

***

12

2%

***

Therapy Areac

With a drug/drug candidate in a specific disease area

          

Metabolic Disorders

-

145

41%

230

35%

498

34%

 

212

29%

 

Cardiovascular

-

116

33%

159

24%

378

26%

 

129

18%

 

Immunology

-

133

37%

256

39%

631

43%

 

257

36%

 

Oncology

-

202

57%

437

66%

1030

70%

 

437

61%

 

Respiratory

-

111

31%

166

25%

428

29%

 

140

20%

 

Musculoskeletal Disorders

-

103

29%

151

23%

381

26%

 

140

19%

 

Infectious Disease

-

142

40%

250

38%

662

45%

*

284

39%

 

Gastrointestinal

-

129

36%

182

28%

453

31%

 

182

25%

 

Central Nervous System

-

172

49%

266

40%

633

43%

 

270

38%

 

Molecule Typec

With a drug/drug candidate of a specific molecule type

          

Gene &Cell

-

45

13%

119

18%

357

25%

**

149

21%

 

Protein

-

69

19%

97

15%

308

21%

**

111

16%

 

Vaccine

-

31

9%

52

8%

169

12%

 

76

11%

 

Anti-Body

-

69

19%

167

25%

506

35%

***

216

31%

 

Peptide

-

50

14%

71

11%

190

13%

 

67

10%

 

Small Molecule

-

241

68%

382

58%

839

58%

 

382

54%

 

Recombinant

-

73

21%

95

14%

244

17%

 

93

13%

 

Biologic

-

7

2%

17

3%

107

7%

***

41

6%

 

Oligonucleotide

-

22

6%

47

7%

154

11%

 

45

6%

 
  1. a We use the pre-outbreak deals as the baseline group to perform chi-squared tests, examining whether the composition of fundraising activities changed during or after the initial global outbreak. The significance of each chi-squared test is denoted by asterisks (*\(P<0.05\), **\(P<0.01\), ***\(P < 0.001\)). No missing values for all variables listed in the table.
  2. b This is a nominal variable, so the percentages of all subjects add up to 100%.
  3. c This is a set of binary variables that are not mutually exclusive and collectively exhaustive. Since companies have more than one drug in their portfolio, each company could be categorized into several therapy areas or molecule types. To address the multiple comparisons issue, we adjust the significance levels per test through Holm’s step-down extension of the Sidak method, controlling the family-wise error rate at 0.05. The unadjusted significance levels are reported in eTable 5 in the online supplement