Published in The Scientific Conquest of Death

Nanomedicine,

Natural Death, and the Quest for

Accident-Limited Healthspans

 

© 2004 Robert A. Freitas Jr.

Author, Nanomedicine

Email:  rfreitas@rfreitas.com

Address:  P.O. Box 605, Pilot Hill, CA  95664

6 January 2004

 

 

Robert A. Freitas Jr., J.D., published the first detailed technical design study of a medical nanorobot ever published in a peer-reviewed mainstream biomedical journal and is the author of Nanomedicine, the first book-length technical discussion of the medical applications of nanotechnology and medical nanorobotics. Volume I was published in October 1999 by Landes Bioscience while Freitas was a Research Fellow at the Institute for Molecular Manufacturing in Palo Alto, California. Freitas published Volume IIA in 2003 and is completing Volumes IIB and III as a Research Scientist at Zyvex Corp., a nanotechnology company headquartered in Richardson, Texas, and is also consulting on molecular assembler design at Zyvex.

 

 

Abstract.  Each year, medically preventable natural deaths impose terrible costs on humanity, including the destruction of vast quantities of human knowledge and human capital.  Future medical technologies, especially nanomedicine, may permit us first to arrest, and later to reverse, the biological effects of aging and most of the current causes of natural death, severing forever the link between calendar time and biological health.  Respirocytes (artificial red cells), microbivores (artificial white cells), and chromallocytes (enabling whole-body chromosome replacement therapy) provide examples of the new therapeutic capabilities that medical nanorobotics can bring in the decades to come, with benefits to include extending the human healthspan at least tenfold beyond its current maximum length.

 

 

Manuscript Text (including Tables, excluding Figures and References):  6,864 words in length

 

 

 

Nanomedicine,

Natural Death, and the Quest for

Accident-Limited Healthspans

 

© 2004 Robert A. Freitas Jr.

Author, Nanomedicine

 

 

 

During the time it takes to read this sentence out loud, a dozen people just perished worldwide.  I think this is an outrage [1] and I want to tell you why I think so – and what nanomedicine and medical nanorobotics can do to help.

 

1.  The Worst Natural Disaster in Human History

 

Let’s start by looking at the dimensions of the human holocaust that we call “natural death” (Table 1).  The death toll in the Year 2001 was worst in India, with almost 9 million casualties.  The bodies were piled nearly as high in China.  The United States fell in third, with 2.4 million fatalities.  The most populous 21 nations lost over half a million lives, each.  These 21 countries represented almost all cultures, races, creeds, and continents.  The human death toll in the Year 2001 from all 227 nations on Earth was nearly 55 million people, of which about 94% or 52 million were not directly caused by human action – that is, not accidents, suicides, homicides or war [2].  In other words, those 52 million deaths were “natural” deaths, all, in principle, directly preventable by medical intervention.

 

Table 1.  Estimated Worldwide Death Toll in 2001

 

 

Country

Deaths

in 2001*

 

Country

Deaths

in 2001*

 

Country

Deaths

in 2001*

 

India

China

U.S.

Russia

Nigeria

Brazil

Indonesia

Pakistan

 

 

8,960,922

8,529,844

2,419,113

2,022,033

1,760,240

 

1,622,562

1,439,159

1,344,938

 

 

 

 

Ethiopia

Bangladesh

Japan

Germany

Zaire (Congo)

Ukraine

South Africa

U.K.

 

1,172,878

1,128,922

1,052,208

863,512

815,100

799,664

732,245

620,339

 

Italy

France

 

Egypt

 

Burma

 

Mexico

 

206 other nations

 

 

TOTAL DEATHS

 

582,568

541,914

 

535,435

 

516,539

 

509,395

17,026,135

 

 

54,995,665

 

* Deaths estimated as midyear population in 2001 for each country [3] multiplied by crude death rate in 2001 for each country [4].

 

Even the most widely recognized greatest disasters in human history (Table 2) pale in comparison to the annual depredations of natural death.  For example, the typhoon that struck Bangladesh in 1970 washed away a million lives.  In 1223 AD, Genghis Khan burned the Persian city of Herat to the ground – it took his Mongol horde an entire week to slaughter the city’s 1.6 million inhabitants.  The Plague carried off 15 million people per year, and World War II took 9 million human beings per year, for half a decade each.  The worldwide influenza pandemic of 1918 exterminated more than 21 million people in a single year.  But even this seemingly greatest of all disasters produced not even half the annual casualties that occur from natural death.  Natural death alone erased 52 million human lives last year.  We can only conclude that natural death is measurably the greatest catastrophe that humankind has ever faced – a catastrophe that continues tormenting us, year after year.

 

Table 2.  Estimated Total Deaths during the Greatest Disasters in Recorded Human History

 

 

 

Disastrous Event in Human History*

 

 

Occurred

in Years:

 

Number of Deaths

per Event (ev)

or per Year (yr)

 

 

NATURAL DEATH (worldwide)

 

Influenza Pandemic (worldwide) [5b]

Great Indian Famine [5b]

The Plague (Black Death) [5b]

World War II (worldwide) [5a]

North China Famine [5b]

Flood, Yellow (Hwang-ho) River, China [5b]

Tai-ping Rebellion, China [5a]

World War I (worldwide) [6b]

Korean War (active period, incl. civilians) [7]

Democide, Nazi Germany [8a]

Nishapur Massacre by Mongol Tului [8b]

Herat Massacre by Jinghiz Khan [8b]

Meru Chahjan Massacre by Mongol Tului [8b]

Typhoon in Bangladesh [5b]

Democide, China (PRC) [8a]

Flood, Yellow (Hwang-ho) River, China [6d]

Democide, USSR [8a]

Earthquake, Shensi Province, China [5b, 6c]

Sacking of Baghdad by Mongol Khulagu [8b]

Democide, Japan [8a]

Democide, Cambodia [8a]

Democide, Poland [8a]

Democide, China (KMT) [8a]

Rebels destroy Kaifeng seawall, China [6c]

Earthquake, Calcutta, India [6d]

French Revolution, Reign of Terror [8d]

Earthquake, Tangshan, China [6c]

Democide, Turkey (Ataturk) [8a]

Democide, Turkey [8a]

Democide, non-Mongol China [8d]

Earthquake, Kansu Province, China [5b, 6c]

Rape of Nanking, China [8e]

Tsunami, Northern China [6d]

Thirty Years’ War [8d]

Earthquake, Tokyo & Yokohama [6d]

Firebombing of Dresden, Germany [5b]

Democide, China (Mao Soviets) [8a]

Typhoon, Bangladesh [6c]

U.S. Civil War [6a]

Tsunami, Friesland, Holland [6c]

Earthquake, Chihii, China [6d]

Flood, Yangtze River, China [6d]

Earthquake, Erzingan, Northern Turkey [6c]

Nuclear bombing of Hiroshima, Japan [5b]

Earthquake, Messina, Sicily [6c]

Democide, Mexico [8a]

Typhoon, Calcutta, India [6c]

Democide, Russia [8a]

Democide, Pakistan [8a]

Earthquake, Quetta, India [6c]

Earthquake, Peru [6c]

Earthquake, Northwestern Iran [6c]

Typhoon, Bangladesh [6c]

Democide, American Indians [8d]

Democide, North Korea [8a]

Democide, African slavery [8d]

Volcanic eruption, Mt. Pelee, West Indies [6c]

Typhoon, Bengal, India [6c]

Democide, Vietnam [8a]

St. Bartholomew’s Day Massacre [8d]

Volcanic eruption, Krakatau [6c]

Earthquake, Bam, Iran [9]

Democide, Indonesia [8a]

Earthquake, Chile [6c]

Earthquake, Assam, India [6c]

Earthquake, Avezzano, Italy [6c]

Democide, China (warlords) [8a]

Earthquake/Tsunami, Sanriku, Japan [6c]

Earthquake, Tabas, Iran [6c]

Earthquake, Mexico City [6c]

Earthquake, Colombia [6c]

Earthquake, Armenia [6c]

Democide, Yugoslavia (Tito) [8a]

Earthquake, Guatemala [6c]

Typhoon, Bangladesh [6c]

Volcanic eruption, Mt. Vesuvius [6c]

Earthquake, Lisbon, Portugal [6c]

Typhoon, Andhra Pradesh, India [6c]

Democide, non-Mongol China [8d]

Democide, Portugal (dictatorship) [8a]

Typhoon, Hong Kong [6c]

Typhoon, Karachi, Pakistan [6c]

Democide, U.K. [8a]

Democide, India [8d]

Christian Crusades [8d]

Aztec human sacrifices [8d]

Democide, Japan [8d]

Albigensian Crusade [8d]

Democide, Ottoman Empire [8d]

Spanish Inquisition [8d]

Democide, Iran [8d]

Democide, Russia [8d]

Extinction of the Neanderthals (est.)

 

 

... 2002, 2003, 2004, …

 

Apr-Nov 1918

1710

1347-1351

1940-1945

 Feb 1877 - Sep 1878

 Aug 1931

1853-1864

1914-1917

1950-1951

1933-1945

ca. 1221

ca. 1223

ca. 1221

12-13 Nov 1970

1949-1987

1887

1917-1987

24 Jan 1556

1258

1936-1945

1975-1979

1945-1948

1928-1949

1642

11 Oct 1737

Jun 1793 - Jul 1794

28 Jul 1976

1919-1923

1909-1918

14th-15th Centuries

16 Dec 1920

Dec 1937

1939

1618-1648

1 Sep 1923

13-15 Feb 1945

1923-1949

30 Apr 1991

1861-1865

1228

12 Sep 1290

1911

27 Dec 1939

6 Aug 1945

28 Dec 1908

1900-1920

5 Oct 1864

1900-1917

1958-1987

31 May 1935

31 May 1970

21 Jun 1990

May-Jun 1965

16th-19th Centuries

1948-1987

1451-1870

8 May 1902

16 Oct 1942

1945-1987

24 Aug 1572

27 Aug 1883

27 Dec 2003

1965-1987

24 Jan 1939

15 Aug 1950

13 Jan 1915

1917-1949

15 Jun 1896

16 Sep 1978

19-20 Sep 1985

14-16 Nov 1985

7 Dec 1988

1944-1987

4 Feb 1976

28-29 May 1963

24 Aug 79 AD

1 Nov 1755

19 Nov 1977

221 BC - 19th Century

1926-1982

18 Sep 1906

15 Dec 1965

1900-1987

13th-19th Centuries

1095-1272

1300-1500

1570-19th Century

1208-1249

12th-19th Centuries

16th-18th Centuries

5th-19th Centuries

10th-19th Centuries

33,000-30,000 BC ?

 

 

~52,000,000/yr

 

21,640,000/ev

20,000,000/ev

15,000,000/yr

9,130,000/yr

5,700,000/yr

3,700,000/ev

2,500,000/yr

2,130,000/yr

1,900,000/yr

1,750,000/yr

1,747,000/ev

1,600,000/ev

1,300,000/ev

1,000,000/ev

927,000/ev

900,000/ev

884,000/yr

830,000/ev

800,000/ev

663,000/yr

531,000/yr

528,000/yr

486,000/yr

300,000/ev

300,000/ev

263,000/ev

242,000/ev

215,000/yr

209,000/yr

200,000/yr

200,000/ev

200,000/ev

200,000/ev

191,700/yr

143,000/ev

135,000/ev

133,000/yr

131,000/ev

106,000/yr

100,000/ev

100,000/ev

100,000/ev

100,000/ev

91,223/ev

85,000/ev

70,900/yr

70,000/ev

62,700/yr

51,800/yr

50,000/ev

50,000/ev

50,000/ev

47,000/ev

45,900/yr

42,600/yr

41,200/yr

40,000/ev

40,000/ev

40,000/yr

36,000/ev

36,000/ev

35,000/ev

33,100/yr

30,000/ev

30,000/ev

29,980/ev

28,400/yr

27,000/ev

25,000/ev

25,000/ev

25,000/ev

25,000/ev

~25,000/ev

24,900/yr

23,000/ev

22,000.ev

20,000/ev

20,000/ev

16,800/yr

13,200/yr

10,000/ev

10,000/ev

9,400/yr

7,500/yr

5,700/yr

5,000/yr

5,000/yr

4,900/yr

2,900/yr

1,800/yr

1,400/yr

1,100/yr

~1,000/yr

 

 

* Democide = the murder of any person or civilian population by (usually nondemocratic) governments, including acts of genocide, politicide, and mass murder, but excluding war deaths [8].

 

 

 

2.  The High Cost to Humanity of Natural Death

 

Of course we’re outraged by natural death because of the obvious personal consequences.  But the cost to humanity of our individual deaths is rarely appreciated, truly staggering, and equally heartbreaking.

 

Each one of us carries within us a complex universe of knowledge, life experience, and human relationships.  Each individual is gifted with unique insights possessed by no one else.  Almost all of this rich treasury of information is forever lost to mankind when any one of us dies.

 

This lost treasury is truly enormous.  If the vast content of each person’s life can be summarized in just one book, then natural death robs us of 52 million books every year, worldwide.  But the U.S. Library of Congress, the world’s largest collection of physical books, holds only 19 million volumes [10].  So each year, we allow a destruction of knowledge equivalent to three Libraries of Congress.  It is as if in 2003, somebody burned the Library of Congress to the ground.  Once in January, then again in May, and again in September.  52 million books go up in flames.  And then in 2004, they burn it down again, three more times.  And then again in 2005.  What’s even worse is that if you agree with me that the sum total of each human mind would really fill many, many books, and not just one, then you must accept that the devastation of knowledge is actually far greater than I’ve suggested here.

 

Besides this staggering sacrifice of information, natural death also destroys wealth on a grand scale.  According to the Lasker Foundation [11], a dozen or so studies since the mid-1970s have found the value for human life is in the range of $3 to $7 million constant dollars, using many different methodologies.

 

More recently, Murphy and Topel [12] at the University of Chicago drew the chart in Figure 1, which I’ve updated to Year 2000 dollars, showing the value of human life at every age for white males.  It recognizes that fewer years remain to us at older ages.  But this is only half of the equation.  The chart in Figure 2 shows my estimate of the number of people that died in the United States in the Year 2000, in each age cohort, year by year, again for white males.  This estimate is computed by multiplying the estimated U.S. population of while males (by age group, 0-110 years) [13] by the death rate by age for U.S. white males (ages 0-80 from Census Bureau [14], ages 81-110 estimated from Vaupel [15]).

 

Figure 1.  U.S. Value of Human Life, by Age, for White Males in the Year 2000 (modified from Murphy and Topel [12])

 

           

 

Figure 2.  Number of Human Deaths in U.S., by Age, for White Males in the Year 2000 (values estimated using data from U.S. Census Bureau [13, 14] and from Vaupel et al [15])

 

           

 

If you multiply the death rate at each age, from the chart in Figure 2, by the dollar value at each age, from the previous chart in Figure 1, you get the economic loss at each calendar age, due to natural death.  The sum of these economic losses divided by the total number of deaths gives you the average economic value of a human life lost, across all the ages of a natural lifespan.  The result is an average value of about $2 million dollars for each (white male) human life lost, with similar conclusions for either gender and for other races.  If we conservatively assume that the population age structure and the age-specific mortality is the same worldwide as in the United States, then the worldwide natural death toll of 52 million people in the Year 2001 represents an economic loss of about $104 trillion dollars every year.

 

How big of an economic calamity is this?  Taking Federal Reserve figures for the total tangible wealth of the United States, including all financial assets, all real estate, and all consumer durables, net of debt [16], and applying the ratio of U.S. GDP [17] to world GDP [18] gives us a crude estimate of total global tangible net worth of $91.35 trillion dollars for the year 2000.  So this means that every year, natural death robs us of human capital roughly equivalent in value to the entire tangible wealth of the world.

 

It is as if in the Year 2003, someone took out a giant broom and swept up all the physical assets of human civilization into a cosmic trash can, and threw it all away.  That’s $104 trillion dollars of financial assets, real estate, and durable goods – gone forever.  And then in 2004, the giant broom sweeps again – another $104 trillion dollars of human capital is destroyed, or three times larger than the $34 trillion dollars of annual economic activity represented by world GDP [18].  Then it happens again in 2005.

 

But the economic disaster caused by natural death is even worse, if you go back further in history.  Since the modern human species first emerged, perhaps 25 millennia ago, 34 billion people have ever walked the Earth [19], and 28 billion of us have already died.  The equivalent total information waste is more than 28 billion books, enough to fill almost 2000 Libraries of Congress.  The equivalent total economic waste is about $60 thousand trillion dollars, enough to rebuild our current tangible civilization 600 times over.  If you carry the tally back a million years, to the very dawn of man, all these figures about double [19].

 

There can only be one logical conclusion:  Natural death is an incredibly costly disaster of unprecedented proportions in human history.

 

So ... what is being done about this ongoing catastrophe?  Let’s take a very broad, statistical look at the progress to date.

 

3.  Current Progress in Eliminating the Disaster of Natural Death

 

The chart shown in Figure 3, compiled from Census Bureau data [20], shows that for the last one-and-a-half centuries, life expectancy at birth has risen dramatically in the United States.  A newborn child in the Year 1850 could only expect to live to 38 years, but should reach almost 75 years today.  To measure longevity, I’m using the Expected Age at Death, which is just your current age plus your remaining life expectancy.

 

Figure 3.  Expected Age at Death (EAD) in the United States (current age + life expectancy) for U.S. White Males

 

 

 

 

 

 

 

But 20th century medical technology has mainly improved the longevity of the very young.  Since 1850, the Expected Age at Death of a 40-year-old has only improved from 68 years to 77 years.  The Expected Age at Death of a 70-year-old has only improved from 80 years to 83 years.  In other words, a 70-year-old’s chances of living another 10 years were about as good in 1850 as they are today.  That’s not much progress.  But let’s take a closer look at the data.

 

The chart in Figure 4 shows the rate of Change in Life Expectancy at birth since 1850, as measured in years of extra life expectancy achieved by medical technology per decade of calendar time [20].  (In all cases from 1850-2000, the rate of change is a positive increase when measured over 10-year spans.)  If we could get to a rate of 10 years of lifespan extension per decade, then medical technology would be extending life exactly as fast as we’re aging, postponing natural death, on average, indefinitely.  We see from Figure 4 that the Change in Life Expectancy improved at only 1 year per decade up until 1890.  After 1890, the Change in Life Expectancy of newborns jumped dramatically, reaching more than 6 years per decade at its peak in 1925.  This was due to the rapid introduction of several basic medical breakthroughs, like public sanitation [21], comprehensive vaccination programs [22], and later, antibiotics [23].

 

Figure 4.  Decadal Increase in U.S. Life Expectancy at Birth for U.S. Males, from 1850 with Projection to 2025

 

 

Note that the rate of Change in Life Expectancy soared from 0.8 to 4 years per decade during 1890 to 1900, a fivefold increase in a 10 year calendar span.  The rate jumped from 2 to 6 years per decade during 1910 to 1925, a threefold increase in a 15 year calendar span.  So we know it’s possible to see very rapid increases in the rate of Change in Life Expectancy, when new technology is brought to bear on the problem.  In other words, history tells us that the current 2.3 year per decade rate of progress could plausibly quadruple to the “magic” 10 years per decade threshold, in the space of just 10-20 years from today, if new resources and new medical technologies are focused on improving human longevity.

 

Worried parents and life insurance salesmen often complain that the young think they’re immortal.  Well, in a sense, the young are almost right!  There are age groups for which it can validly be said that extreme life extension has already been achieved, using existing medical technology.  To better appreciate this accomplishment, we need to spend one paragraph briefly discussing death rates.

 

The chart in Figure 5 shows the aggregate death rate for all males, at all ages, in the United States, from 1850 to 2000 [24].  In 1850, each male had a 2 percent chance of dying in the next year.  By 2000, each male had a 1 percent chance of dying in the next year.  So over this 150-year time span, the death rate was cut in half.  As a result, the life expectancy from birth [25] has approximately doubled, from 38 years in 1850 to almost 75 years in 2000, as shown by the black curve in Figure 6.  A very simple formula, written in red below, can be devised for estimating the Expected Age at Death.  This formula captures the simple truth that, roughly speaking, cutting the death rate in half doubles the life expectancy, as measured from the current age of the individual.  The formula assumes a single net death rate, for a whole population of mixed ages.  This is an important point, because the natural death rate in humans usually depends on our physiological age.  Death rates typically rise, log-linearly, with advancing age, except at the oldest ages.  (The documented deceleration of mortality in humans above age 109 (Figure 7), reported by Vaupel et al [16], and in medflies above age 60 days, reported by Carey et al [26], is one of the most intriguing recent findings in longevity research). 

 

 

Figure 5.  Death Rate (DR) for U.S. Males, All Ages

 

 

Figure 6.  Estimated vs. Actual Expected Age at Death for U.S. Males, at Birth

 

Figure 7.  Death Rate Deceleration in Older Humans -- Vaupel’s Data [16] (black curve, ages 80-114), Census Bureau Data [24] (black curve, ages 0-79), and One Possible Extrapolation of the Trend (smooth red curve, ages 108-125)

 

Now let’s return to my claim that there are age groups that have already achieved extreme life extension, using existing medical technology.  Medical technology has had its greatest impact to date in preventing infant mortality, especially between the ages of 1 to 4.  Our dramatic success in reducing the death rate in this youthful age cohort [27] is illustrated in Figure 8.  For the Year 1850, a young child in this age cohort had a 2.4% probability of dying in the next year.  Today, the probability of dying in the next year for these children has been slashed from 2.4% to 0.04%.  That’s a phenomenal 60-fold reduction.

 

Figure 8.  Death Rate (DR) in U.S. Males, Ages 1-4

 

What if future medical technologies permit us first to arrest, and later to reverse, the biological effects of aging?  In such an era, our bodies would no longer tumble down a staircase of degeneration and frailty.  Instead, our statistical death rate would take on some approximately fixed value that’s appropriate for our physiological-age cohort, not our calendar-age cohort.  Biological age would no longer march in lockstep with calendar age.

 

So, how much longer might we live, if we could just keep the bodies we had when we were young?  Figure 9 shows that in the Year 1850, the death rate for a U.S. male between the ages of 1 and 4 implied an Expected Age at Death, according to our formula (see Figure 6), of only 31 years.  That is, in 1850, a child that could remain perpetually 1-4 years old physiologically, would have died, on average, after 31 calendar years.  Early childhood was still very unhealthy and dangerous in those days.

 

Figure 9.  Expected Age at Death, Assuming Age-Invariant Death Rate, for U.S. Males, Ages 1-4

 

 

But as medical technology slowly improved, childhood became vastly less dangerous.  Most of the specific medical causes of early childhood death have now been analyzed and conquered.  As a result, a child that could remain perpetually 1-4 years old biologically today would not die, on average, until he or she reached the calendar age of 1800 years.  Death would usually come from some form of non-medical accident, which is the leading cause of death up to age 44 [28].

 

Of course, most of us aren’t 1-4 years old.  How long would we live if we could halt any further biological aging of our bodies right now, at our current age?  The answer for various biological age cohorts, up to 44 years old [27], is shown in Figure 10.  The 10-year-olds among us would fare the best, reaching an average Expected Age at Death exceeding 3000 calendar years.  The 20-year-olds would make it to 600 calendar years.  Life has even become less dangerous for the 40-year-olds, who could survive to an average calendar age of 300 years in today’s medical environment, if further biological aging could be immediately halted.  These are remarkable achievements of medical technology compared to the Year 1850, a time when none of these groups would have survived more than 80-100 calendar years.  Note that all of these curves – and most especially the youngest cohorts – began their steep climbs into extended longevity during the latter half of the 19th century.

 

Figure 10.  Expected Age at Death, Assuming Age-Invariant Death Rate, for U.S. Males, Ages 1-44

 

If you’re over 45 [27], the picture is not yet so bright (Figure 11).  Non-aging biological 50-year-olds would live to a calendar age of 178 years.  Non-aging 60-year-olds could only expect to survive to 113 calendar years in the current medical environment.  But the news is not all bad for the elders.  The death rate for 80-year-old U.S. males actually fell by 45% during the last century.  So some progress is definitely being made.  The problem is that the absolute natural death rate is still so high among the elderly that the Expected Age at Death has not yet significantly improved.

 

Figure 11.  Expected Age at Death, Assuming Age-Invariant Death Rate, for U.S. Males, Ages 35-84

 

 

 

Now, you remember those Expected Age at Death curves for the youngsters that began their steep climb into extended longevity in the late 19th Century?  The biggest gains were in the 1-10 year old cohorts, where death rates fell 30- to 60-fold.  These gains began at a time when this age cohort made up 20% to 30% of the U.S. population.  Early deaths in this gigantic demographic bulge were of great concern to medical researchers at the time, who lavished their limited resources on solving this problem.

 

I think history is about to repeat, this time at the opposite end of the age scale.  In the United States, people over 60 years of age already make up the single largest cohort at 16.5%, and this cohort grows to 20% to 30% of the U.S. population after 2015, and for decades beyond (Figure 12).  As before, this demographic bulge (Figure 12) will focus research scientists and research dollars towards solving the problem of premature death – but this time, among the very old.

 

Figure 12.  Age Distribution of U.S. Population, 1850-2030 [29]

 

4.  Molecular Nanotechnology and Nanomedicine

 

The greatest advances in halting biological aging and preventing natural death are likely to come from the fields of biotechnology and nanotechnology – that is, from nanomedicine.  Nanomedicine is most simply and generally defined as the preservation and improvement of human health, using molecular tools and molecular knowledge of the human body [30].

 

In the near term, say, the next 5 years, the molecular tools of nanomedicine will include biologically active materials with well-defined nanoscale structures, such as dendrimer-based organic devices and pharmaceuticals based on fullerenes and organic nanotubes.  We should also see genetic therapies and tissue engineering becoming more common in medical practice, which can contribute a little to life extension at the oldest ages.

 

In the mid-term, the next 5 or 10 years or so, knowledge gained from genomics and proteomics will make possible:  (1) new treatments tailored to specific individuals, (2) new drugs targeting pathogens whose genomes have now been decoded, (3) stem cell treatments to repair damaged tissue, replace missing function, or slow aging, and (4) biological robots made from bacteria and other motile cells that have had their genomes re-engineered and re-programmed.  We could also see artificial organic devices that incorporate biological motors or self-assembled DNA-based structures for a variety of useful medical purposes.  We may even begin to see targeted anti-aging treatments which address each of the seven specific forms of cellular damage that produce pathologies leading to natural death, as described by Aubrey de Grey and colleagues [31], although there remain many institutional obstacles to direct progress via this conventional approach [32].

 

In the farther term, perhaps somewhere in the 10 or 20 year time frame, the first fruits of molecular nanorobotics should begin to appear in the medical field.  My own theoretical work in nanomedicine has concentrated on medical nanorobotics using diamondoid materials and nanoparts.  This area, though clinically the most distant and still mostly theoretical, holds the greatest promise for health and life extension.  With medical nanorobotics, we will gain the technological ability to perform specific internal repairs on individual cells in real time, thus largely eliminating all major causes of natural biological death.

 

The early theoretical work done by Drexler and Merkle, including most prominently a collection of bearings, gears, and other possible nanorobot parts, is well-known [33].  Their most complex design was a nanoscale neon pump (Figure 13) having over 6,000 atoms, which was later simulated by computational chemists at California Institute of Technology [34].  The device could serve either as a pump for neon gas atoms or (if run backwards) as a motor to convert neon gas pressure into rotary power.  The CalTech researchers reported that preliminary molecular dynamics simulations of the device showed that it could indeed function as a pump, although “structural deformations of the rotor can cause instabilities at low and high rotational frequencies.”  The motor was not particularly energy efficient – but it worked.

 

Figure 13.  Side views of a 6165-atom neon gas pump/motor [35].  © Institute for Molecular Manufacturing (www.imm.org).

 

 

The ultimate goal of molecular nanotechnology is to develop a manufacturing technology able to inexpensively manufacture most arrangements of atoms that can be specified in molecular detail.  Building medical nanorobots, each made of millions or billions of atoms, in batches of trillions of devices cheaply enough to be practical for medical therapies requires some new kind of manufacturing technology.  Molecular manufacturing will be the ultimate manufacturing technology in terms of its precision, flexibility, and low cost.  Two central mechanisms have been proposed to achieve these goals at the molecular scale:  (1) programmable positional assembly including, for example, fabrication of diamond structures using molecular feedstock, and (2) massive parallelism of all fabrication and assembly processes.

 

As machine structures become more complex, getting all the parts to spontaneously self-assemble in the right sequence is increasingly difficult.  To build complex structures, it makes more sense to design a mechanism that can assemble a molecular structure by what is called positional assembly – that is, picking and placing molecular parts.  A device capable of positional assembly at the molecular scale would work much like the robot arms that manufacture cars on automobile assembly lines in Detroit, or which insert electronic components onto computer circuit boards with blinding speed in Silicon Valley.  Using the positional assembly approach, the robot manipulator picks up a part, moves it to the workpiece, and installs it.  The robot then repeats the procedure over and over with many different parts until the final product is fully assembled.

 

In order to build durable nanorobots, we first must be able to fabricate parts made of diamond, sapphire, or similar strong materials.  The controlled addition of carbon atoms to a growth surface of the diamond crystal lattice is called diamond mechanosynthesis [36, 37].  In 2003, Merkle and Freitas [36] proposed a new family of mechanosynthetic tools intended to be employed for the placement of two carbon atoms – a CC “dimer” – onto a growing diamond surface at a specific site (Figure 14).  These tools should be stable in vacuum and should be able to hold and position a CC dimer in a manner suitable for positionally controlled diamond mechanosynthesis at liquid nitrogen temperatures and possibly even at room temperatures.  The function of a dimer placement tool is to position the dimer, then bond the dimer to a precisely chosen location on a growing diamond molecular structure, and finally to withdraw the tool – leaving the dimer behind on the growing structure.  The diamond structure is then is built up, dimer by dimer, until a complete molecularly precise nanopart has been fabricated.

 

Figure 14.  Merkle-Freitas mechanosynthesis dimer placement tooltip molecule (above) used in a dimer placement sequence (below) on a diamond surface prepared with radicals [38]

Both the fabrication of nanoparts and the assembly of nanoparts into working nanorobots must be automated and must employ massive parallelism to be practical.  There must be many hands at work simultaneously.  Without this parallelism, there would be too many atoms per device (millions/billions) and too many devices needing to be assembled per application (trillions).  New techniques for massively parallel positional assembly are being developed, including massively parallel manipulator arrays and self-replicating systems.  One example of parallel assembly arrays, called “exponential assembly,” has been proposed and patented by Zyvex [39].  There have also been many proposals for self-replicating systems known as molecular assemblers, tiny machines that could manufacture nanorobots with molecular precision [40].

 

What sorts of medical nanorobots could we build, and what would they do, if we could build them?  The first simple device that I designed 9 years ago was the respirocyte, an artificial red blood cell (Figure 15).  I show them blue in color, because part of the outermost shell is made of sapphire, a tough ceramic made of aluminum and oxygen atoms which is almost as hard as diamond.  Natural red cells carry oxygen and carbon dioxide throughout the human body.  We have about 30 trillion of these cells in all our blood.  Half our blood volume is red cells.  Each red cell is about 3 microns thick and 8 microns in diameter.  Respirocytes are much smaller than red cells – only 1 micron in diameter, about the size of a bacterium.  Respirocytes are microscopic pressure tanks with a hull made mostly of flawless diamondoid crystal.  These tanks could be safely charged up to 100,000 atmospheres of pressure, but we’re conservative and only run them up to 1000 atmospheres.

 

Figure 15.  An artificial red cell – the respirocyte [41].  Designer Robert A. Freitas Jr.  ©1999 Forrest Bishop.  Used with permission.

 

 

 

Respirocytes are self-contained nanorobots built of 18 billion precisely arranged structural atoms.  Each device has an onboard computer and an onboard powerplant.  Most importantly, molecular pumps are arranged on the surface to load and unload gases from the pressurized tanks.  Tens of thousands of individual pumps, called molecular sorting rotors, cover a large fraction of the hull surface of the respirocyte (Figure 16).  As the rotor turns, molecules of oxygen (O2) or carbon dioxide (CO2) may drift into their respective binding sites on the rotor surface and be carried into (or out of) the respirocyte interior.  There are 12 identical pumping stations laid out around the equator of the respirocyte, with oxygen rotors on the left, carbon dioxide rotors on the right, and water rotors in the middle.  Temperature and concentration sensors tell the devices when to release or pickup gases.  Each station has special pressure sensors to receive ultrasonic acoustic messages, so doctors can tell the devices to turn on or off, or change their operating parameters, while the nanorobots are inside a patient.  The shaded area at left is the O2 storage tank, the area at right is the CO2 tank, the black dot at the center is the computer, and the open volume around the computer can be a vacuum, or can be filled or emptied with water.  This allows the device to control its buoyancy very precisely and provides a crude but simple method for removing respirocytes from the blood using a centrifuge.

 

Figure 16.  Internal cutaway view of respirocyte – equatorial (left) and polar (right) view [41].  ©1996 Robert A. Freitas Jr.

 

We can’t build respirocytes today, but when we can build them, they could be used as an emergency treatment at the scene of a fire, where the victim has been overcome by carbon monoxide poisoning.  In an animation [42] from the PBS documentary “Beyond Human”, 5 cubic centimeters of respirocyte-containing fluid are injected into the patient’s vein.  After passing through the pulmonary bed, the heart, and some major arteries, the respirocytes make their way into smaller, and smaller, blood vessels.  After about 30 seconds, they reach the patient’s capillaries and begin releasing life-giving oxygen to starving tissues.  In the tissues, oxygen is pumped out of the device by the sorting rotors on one side.  Carbon dioxide is pumped into the device by the sorting rotors on the other side, one molecule at a time.  Half a minute later, when the respirocyte reaches the patient’s lungs, these same rotors reverse their direction of rotation, recharging the device with fresh oxygen and dumping the stored CO2, which can then be exhaled by the patient.

 

Only 5 cc’s of respirocytes, just 1/1000th of our total blood volume, could duplicate the oxygen-carrying capability of the entire human blood mass.  Each respirocyte transports hundreds of times more physiologically available oxygen molecules than an equal volume of natural red blood cells.  A half a liter of respirocytes, the most that could possibly be safely added to our blood, would allow a person to hold his breath at the bottom of a swimming pool for up to 4 hours, or to sprint at top Olympic speed for up to 12 minutes, without taking a breath.

 

Another medical nanorobot I designed more recently is the microbivore (Figure 17) – an artificial white cell [43].  One main task of natural white cells is to absorb and digest microbial invaders in the bloodstream.  This is called phagocytosis.  Microbivore nanorobots would also perform phagocytosis, but would operate much faster, more reliably, and under human control.  Like the respirocyte, the microbivore is much smaller than a red blood cell but is more complex than the respirocyte, having about 30 times more atoms involved in its construction.

 

Figure 17.  An artificial white cell – the microbivore [43].  Designer Robert A. Freitas Jr., illustrator Forrest Bishop.  ©2001 Zyvex Corp.

 

 

 

 

 

 

The microbivore device is a flattened sphere with the ends cut off.  It measures over 3 microns in diameter along its major axis and 2 microns in diameter along its minor axis.  This size helps to ensure that the nanorobot can safely pass through even the narrowest of human capillaries and other tight spots in the spleen (e.g., the interendothelial splenofenestral slits [44]) and elsewhere in the human body.  The microbivore has a mouth with an irising door, called the ingestion port, where microbes are fed in to be digested.  The microbivore also has a rear end, or exhaust port.  This is where the completely digested remains of the pathogen are expelled from the device.  The rear door opens between the main body of the microbivore and a tail-cone structure.  Inside the microbivore, there are two concentric cylinders.  The bacterium is minced into little pieces in the morcellation chamber, the smaller inner cylinder, and then the remains are pushed into the digestion chamber, the larger outer cylinder.  In a preprogrammed sequence engineered digestive enzymes are added, then removed, using an array of sorting rotors.  In just 30 seconds these enzymes reduce the microbe’s remains to simple chemicals – like amino acids, free fatty acids, and simple sugars – which are then expelled harmlessly from the device.  A human neutrophil, the most common type of leukocyte or white cell, can also capture and engulf a microbe in a minute or less, but complete digestion and excretion of the bug’s remains can take an hour or longer. 

 

But the first thing a microbivore has to do is reliably acquire a pathogen to be digested.  If the correct bacterium bumps into the nanorobot surface, reversible binding sites on the microbivore hull can recognize and weakly bind to the bacterium.  A set of 9 different antigenic markers should be specific enough, since all 9 must register a positive binding event to confirm that a targeted microbe has been caught.  There are 20,000 copies of these 9-marker receptor sets, distributed in 275 disk-shaped regions across the microbivore surface.  These receptors are the multicolored dots you see around the perimeter of each disk.  Inside the receptor ring are more rotors to absorb glucose and oxygen from the bloodstream for nanorobot power.  At the center of each receptor disk is a grapple silo (see below);  each disk is 150 nanometers in diameter.

 

Once a bacterium has been captured by the reversible receptors, telescoping grapples rise up out of the microbivore surface and attach to the trapped bacterium.  The microbivore grapples are modeled after a watertight manipulator arm originally designed by Drexler [45] for nanoscale manufacturing.  This arm is about 100 nanometers long and has various rotating and telescoping joints that allow it to change its position, angle, and length.  But the microbivore grapples need a greater reach and range of motion, so they’re longer and more complex, with many additional joints.  After rising out of its silo, a grapple arm can execute complex twisting motions, and adjacent grapple arms can physically reach each other, allowing them to hand off bound objects as small as a virus particle.  Grapple handoff motions can transport a large rod-shaped bacterium from its original capture site forward into the mouth of the microbivore device.  The bug is rotated into the proper orientation as it approaches the open mouth, as depicted in Figure 17.

 

Our natural white cells – even when aided by antibiotics – can sometimes take weeks or months to completely clear bacteria from the bloodstream.  By comparison, a single terabot dose of microbivores should be able to fully eliminate bloodborne pathogens in just minutes or hours, even in the case of locally dense infections.  Microbivores would be up to ~1000 times faster-acting than natural leukocytes.  They’d digest almost 100 times more microbial material than an equal volume of natural white cells could digest, in any given time period.

 

Even more powerful applications – most importantly, involving cellular replacement or repair – are possible with medical nanorobotics.  For example, most diseases involve a molecular malfunction at the cellular level, and cell function is significantly controlled by gene expression of proteins.  As a result, many disease processes are driven either by defective chromosomes or by defective gene expression.  So in many cases it may be most efficient to extract the existing chromosomes from a diseased cell and insert fresh new ones in their place.  This procedure is called “chromosome replacement therapy.”

 

During this procedure, your replacement chromosomes are first manufactured to order, outside of your body, in a clinical benchtop production device that includes a molecular assembly line.  Your individual genome is used as the blueprint.  If the patient wants, acquired or inherited defective genes could be replaced with nondefective base-pair sequences during the chromosome manufacturing process, thus permanently eliminating any genetic disease – including conditions related to aging.  Nanorobots called chromallocytes [46], each carrying a single copy of the revised chromosomes, are injected into the body and travel to the target tissue cells.  Following powered cytopenetration and intracellular transit to the nucleus, the chromallocytes remove the existing chromosomes and then install the properly methylated replacement chromosomes in every tissue cell of your body (requiring a total dose of several trillion nanorobots), then exit the cell and tissue, re-enter the bloodstream, and finally eliminate themselves from the body through the kidneys.

 

5.  Dechronification:  A Treatment for the Disease of Natural Death

 

The end result of all these nanomedical advances will be to enable a process I call “dechronification” – or, more colloquially, “rolling back the clock.”  I see no serious ethical problems with this.  According to the volitional normative model of disease that is most appropriate for nanomedicine [30], if you’re physiologically old and don’t want to be, then for you, oldness and aging – and natural death – are a disease, and you deserve to be cured.  After all, what’s the use of living many extra hundreds of years in a body that lacks the youthful appearance and vigor that you desire?

 

Dechronification will first arrest biological aging, then reduce your biological age by performing three kinds of procedures on each one of the 4 trillion tissue cells in your body:

 

First, a respirocyte- or microbivore-class device will be sent to enter every tissue cell, to remove accumulating metabolic toxins and undegradable material.  Afterwards, these toxins will continue to slowly re-accumulate as they have all your life, so you’ll probably need a whole-body cleanout to prevent further aging, maybe once a year.

 

Second, chromosome replacement therapy can be used to correct accumulated genetic damage and mutations in every one of your cells.  This might also be repeated annually, or less often.

 

Third, persistent cellular structural damage that the cell cannot repair by itself such as enlarged or disabled mitochondria can be reversed as required, on a cell by cell basis, using cellular repair devices.  We’re still a long way from having complete theoretical designs for many of these machines, but they all appear possible in theory.  By the time our molecular manufacturing capability progresses to the degree necessary to begin building medical nanorobots, probably in the next 10-20 years, we will have good designs for cell repair devices.

 

The net effect of these interventions will be the continuing arrest of all biological aging, along with the reduction of current biological age to whatever new biological age is deemed desirable by the patient, severing forever the link between calendar time and biological health.  These interventions may become commonplace, several decades from today.

 

Using annual checkups and cleanouts, and some occasional major repairs, your biological age could be restored once a year to the more or less constant physiological age that you select.  I see little reason not to go for optimal youth – though trying to maintain your body at the ideal physiological age of  10 years old might be difficult and undesirable for other reasons.  A rollback to the robust physiology of your late teens or early twenties would be easier to maintain and much more fun.  That would push your Expected Age at Death up to around 700-900 calendar years (Figure 18).  You might still eventually die of accidental causes, but you’ll live ten times longer than you do now.

 

Figure 18.  Expected age at death after dechronification

 

 

 

How far can we go with this?  Well, if we can eliminate 99 percent of all medically preventable conditions that lead to natural death [2], your healthy lifespan – or healthspan – should increase to about 1100 years (Table 3).  It may be that you’ll find it hard to coax more than a millennium or two out of your original biological body, because deaths from suicides and accidents have remained stubbornly high for the last 100 years, falling by only one-third during that time.  But our final victory over the scourge of natural biological death, which we shall achieve later in this century, should extend the healthspan of normal human beings by at least ten- or twenty-fold beyond its current maximum length.

 

Table 3.  Nanomedical Limits to Human Biological Healthspan following the Nanomedical Conquest of Natural Death

 

 
Current Cause of Death Cumulatively Eliminated

 

Net Remaining Death Rate

(deaths per

person-year)

 

Expected

Age at Death (calendar

years)

 

 

NONE (death rates same as in Year 2000)

 

10% of medically preventable conditions eliminated

50% of medically preventable conditions eliminated

90% of medically preventable conditions eliminated

 

99% of medically preventable conditions eliminated

 

99% of vehicular accidents eliminated

99% of suicides, homicides, executions eliminated

Age-arrested body of 10-year-old boy in Year 2000

99% of non-vehicular accidents eliminated

 

 

 

0.008647

 

0.007837

0.004595

0.001353

 

0.000624

 

0.000465

0.000286

0.000130

0.000086

 

 

 

 

 

80

 

88

151

512

 

1,110

 

1,490

2,420

5,340

8,000

 

 

 

One can hope that the rate of suicides might be greatly reduced, with so much to look forward to, and with new nanomedical treatments for debilitating mental states becoming available.  Nanotechnology can also improve the overall safety of our material environment – e.g., by making possible virtually crash-free, crash-safe cars and aircraft, buildings (including houses) that incorporate active safety devices, advanced nanomedicine for severe trauma anticipation and recovery, and the like – leading to vastly fewer deaths from accidents.  Finally, genetic modifications or nanomedical augmentations to the human body [47] may extend healthy lifespans still further, to a degree that cannot yet be accurately predicted.

 

Notes and References

 

1.  This chapter was adapted and updated from a lecture entitled “Death is an Outrage!”, delivered by the author at the Fifth Alcor Conference on Extreme Life Extension, Newport Beach, CA, on 16 November 2002.

 

2.  “Table 105.  Deaths and Death Rates by Selected Causes:  1990 to 1998,” Vital Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, p. 79.

 

3.  “Table 1327.  Population by Country:  1990 to 2010,” Comparative International Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, pp. 831-833.

 

4.  “Table 1330.  Vital Statistics by Country:  2001 and 2010,” Comparative International Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, p. 835.

 

5.  Norris McWhirter, Ross McWhirter, eds., The 1974 Guinness Book of World Records, Revised American Edition, Sterling Publishing Co., New York, 1973, p. 378 (a), pp. 484-485 (b).

 

6.  The 1994 Information Please Almanac, Atlas and Yearbook, 47th Edition, Houghton Mifflin Company, New York, 1994, p. 385 (a), p. 389 (b), pp. 401-405 (c), p. 812 (d).

 

7.  Combatant deaths included 136,858 South Koreans, 54,268 Americans, and 3,687 other UN soldiers, or 194,813 combatants (“The Korean War: Forgotten No More,” http://www.koreasociety.org/MAIN/KWarConferenceRpt/KW_Abstracts7.htm), plus up to 2-3 million civilians in both North and South Korea (Jon Halliday, Bruce Cumings, Korea: The Unknown War, Pantheon Books, New York, 1988, p. 200;  see also “Korea: The Right War? At What Price?” Digital History, http://www.digitalhistory.uh.edu/historyonline/con_korea.cfm).

 

8.  R.J. Rummel, Death By Government, Transaction Publishers, New Brunswick, NJ, 1994, p. 4 (a), pp. 48-50 (b), p. 60 (c), p. 70 (d), p. 148 (e).

 

9.  Contemporaneous media reports, December 2003 – January 2004.

 

10.  “Fascinating Facts About the Library of Congress,” The Library of Congress website;  http://www.loc.gov/homepage/fascinate.html

 

11.  “Exceptional Returns: The Economic Value of America’s Investment in Medical Research,” Funding First Reports, Lasker Medical Research Network, Lasker Foundation, May 2000, p. 5;  http://www.laskerfoundation.org/reports/pdf/exceptional.pdf

 

12.  Kevin M. Murphy, Robert Topel, “The Economic Value of Medical Research,” Funding First Reports, Lasker Medical Research Network, Lasker Foundation, March 1998, revised September 1999;  http://www.laskerfoundation.org/reports/pdf/economicvalue.pdf

 

13.  Jennifer Cheeseman Day, “Table 2.  Projections of the Population, by Age, Sex, Race, and Hispanic Origin, for the United States:  1993 to 2050 (Middle Series) – July 1, 2000, White Male,” Population Projections of the United States, by Age, Sex, Race, and Hispanic Origin:  1993 to 2050, Current Population Reports, Report No. P25-1104, Bureau of the Census, U.S. Department of Commerce, November  1993, p. 26.

 

14.  “Table 98.  Expectation of Life and Expected Deaths by Race, Sex, and Age:  1998,” Vital Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, p. 74.

 

15.  James W. Vaupel, J.R. Carey, K. Christensen, T.E. Johnson, A.I. Yashin, N.V. Holm, I.A. Iachine, V. Kannisto, A.A. Khazaeli, P. Liedo, V.D. Longo, Y. Zeng, K.G. Manton, J.W. Curtsinger, “Biodemographic trajectories of longevity,” Science 280(8 May 1998):855-860.

 

16.  U.S. national net worth in current dollars was $20.0141 trillion in 1994 (“Table B.11 Domestic Wealth with Tangible Assets at Current Cost, Year-End Outstandings,” Balance Sheets for the U.S. Economy, 1945-1994, Release C.9, Flow of Funds, 8 June 1995, Board of Governors of the Federal Reserve System, Washington, DC, 1995, p. 7);  applying a +3%/yr inflation factor and a +2%/yr real growth rate during 1995-2000 (Federal Reserve Bulletins, 1995-2000) yields an estimate for U.S. national net worth of $26.82 trillion in the year 2000.

 

17.  The 2000 U.S. GDP was $9.896 trillion in constant year 2000 dollars, according to:  “Table 1340.  Gross Domestic Product (GDP) by Country:  1995 to 2000,” Comparative International Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, p. 841.

 

18.  The 1999 GDP for 197 countries was $27.5769 trillion in constant 1990 dollars, according to: “Table B2.  World Gross Domestic Product at Market Exchange Rates, 1990-1999,” Department of Energy (DOE);  http://www.eia.doe.gov/emeu/iea/tableb2.html.  Using Census Bureau data [17] to estimate the world GDP deflator, this figure for world GDP is estimated as equivalent to $33.7080 trillion in constant year 2000 dollars, for the year 2000.

 

19.  Cumulative summation of year-by-year population estimates interpolated from the Kremer Series yields estimate of 34.5355 billion people that have lived from 25,000 BC to 2000 AD;  a more expansive definition of “human” produces a similar cumulative estimate of 59.5522 billion “human” individuals that have ever lived since 1,000,000 BC.  See the Kremer Series in:  Michael Kremer, “Population Growth and Technical Change, One Million B.C. to 1990,” Quarterly Journal of Economics 108(August 1993):681-716.

 

20.  Data for years 1850-1895 for At Birth, Age 40, and Age 70 are for all males in Massachusetts;  source:  “Series B 126-135.  Expectation of Life at Specified Ages, by Sex, for Massachusetts:  1850 to 1949-51,” Vital Statistics, Historical Statistics of the United States:  Colonial Times to 1970, U.S. Department of Commerce, Bureau of the Census, 1989, p. 56 (Series 126, 130, and 134);  data for 1860-1875 and 1885 are interpolated.  Data for years 1900-1965 for At Birth, Age 40, and Age 70 are for all U.S. white males;  source:  “Series B 116-125.  Expectation of Life at Specified Ages, by Sex and Race:  1900-1970,” Vital Statistics, Historical Statistics of the United States:  Colonial Times to 1970, U.S. Department of Commerce, Bureau of the Census, 1989, p. 56 (Series 116, 120, and 124).  Data for years 1970-2000 for At Birth, Age 40, and Age 70 are for all U.S. white males;  source:  “Table 96.  Expectation of Life at Birth, 1970 to 1999, and Projections, 2000 to 2010,” Vital Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, p. 73.

 

21.  The report by Edwin Chadwick, “Sanitary Conditions of the Labouring People of Great Britain,” submitted to the Council of London in 1842, ushered in the Great Sanitation Revolution in the Western world, e.g., the Public Health Acts of 1845 and 1875 in Britain.  The first comprehensive system of underground sewers in the United States was installed in Chicago in the 1850s;  the opening of the Sanitary and Ship Canal in 1900 resulted in 91% drop in the rate of typhoid deaths in the city by 1908.  Source:  Steve Jones, John Waller, “Down the Drain.  Four: The Big Ditch,” Chicago Public Library Digital Collections, 1 October 1999;  http://www.chipublib.org/digital/sewers/history4.html

 

22.  For example, deaths among children under age 15 fell from 90 per 100,000 in 1895 to 30 per 100,000 in 1925, due to the introduction of diphtheria vaccine;  source:  T. McKeown, The Role of Medicine:  Dream, Mirage, or Nemesis?, Princeton University Press, Princeton, New Jersey, 1979.   See chart in:  Robert A. Freitas Jr., “Figure 1.2,” Nanomedicine, Volume I:  Basic Capabilities, Landes Bioscience, Georgetown, TX, 1999;  http://www.nanomedicine.com/NMI/Figures/1.2.htm

 

23.  Antibiotics were widely introduced in the U.S. during 1935-1945;  source:  Robert A. Freitas Jr., “Section 1.2.1.12,” Nanomedicine, Volume I:  Basic Capabilities, Landes Bioscience, Georgetown, TX, 1999;  http://www.nanomedicine.com/NMI/1.2.1.12/1.2.htm#p4

 

24.  Data for years 1860-1895 are for all males in Massachusetts;  source:  “Series B 193-200.  Death Rate, by Sex and by Selected Cause, for Massachusetts:  1860 to 1970,” Vital Statistics, Historical Statistics of the United States:  Colonial Times to 1970, U.S. Department of Commerce, Bureau of the Census, 1989, p. 63 (Series 194).  Data for years 1900-1965 are for all U.S. males;  source:  “Series B 181-192.  Death Rate, by Age and Sex:  1900-1970,” Vital Statistics, Historical Statistics of the United States:  Colonial Times to 1970, U.S. Department of Commerce, Bureau of the Census, 1989, p. 61 (Series 181).  Data for years 1970-2000 are for all U.S. males;  source:  “Table 100.  Death Rates by Age, Sex, and Race:  1970 to 1998,” Vital Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, p. 75;  year 1998 datum used as estimate for year 2000.

 

25.  Data for years 1850-1895 for At Birth are for all males in Massachusetts;  source:  “Series B 126-135.  Expectation of Life at Specified Ages, by Sex, for Massachusetts:  1850 to 1949-51,” Vital Statistics, Historical Statistics of the United States:  Colonial Times to 1970, U.S. Department of Commerce, Bureau of the Census, 1989, p. 56 (Series 126);  data for 1860-1875 and 1885 are interpolated.  Data for years 1900-1965 for At Birth are for all U.S. white males;  source:  “Series B 116-125.  Expectation of Life at Specified Ages, by Sex and Race:  1900-1970,” Vital Statistics, Historical Statistics of the United States:  Colonial Times to 1970, U.S. Department of Commerce, Bureau of the Census, 1989, p. 56 (Series 116).  Data for years 1970-2000 for At Birth are for all U.S. white males;  source:  “Table 96.  Expectation of Life at Birth, 1970 to 1999, and Projections, 2000 to 2010,” Vital Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, p. 73.

 

26.  J.R. Carey. P. Liedo, D. Orozco, J.W. Vaupel, “Slowing of mortality rates at older ages in large medfly cohorts,” Science 258(16 October 1992):457-461.

 

27.  Data for years 1865-1895 are for all persons in Massachusetts;  source:  “Series B 201-213.  Death Rate, by Age, for Massachusetts:  1865 to 1900,” Vital Statistics, Historical Statistics of the United States:  Colonial Times to 1970, U.S. Department of Commerce, Bureau of the Census, 1989, p. 63 (Series 203-213).  Data for years 1900-1965 are for all U.S. males;  source:  “Series B 181-192.  Death Rate, by Age and Sex:  1900-1970,” Vital Statistics, Historical Statistics of the United States:  Colonial Times to 1970, U.S. Department of Commerce, Bureau of the Census, 1989, p. 61 (Series 183-191).  Data for years 1970-2000 are for all U.S. males;  source:  “Table 100.  Death Rates by Age, Sex, and Race:  1970 to 1998,” Vital Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, p. 75;  year 1998 datum used as estimate for year 2000.

 

28.  “Table 107.  Death by Selected Causes and Selected Characteristics:  1998,” Vital Statistics, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, p. 81.

 

29.  Data from:  “Series A 119-134.  Population, by Age, Sex, Race, and Nativity: 1790 to 1970,” Population, Historical Statistics of the United States:  Colonial Times to 1970, U.S. Department of Commerce, Bureau of the Census, 1989, p. 15;  and from: “Table 12.  Resident Population by Age and Sex:  1980 to 1999” and “Table 13.  Resident Population Projections by Sex and Age:  2005 to 2050,” Population, Statistical Abstract of the United States: 2001, U.S. Census Bureau, 2001, pp. 14, 15;  year 1999 datum used as estimate for year 2000.

 

30.  Robert A. Freitas Jr., “Section 1.2.2 Volitional Normative Model of Disease,” Nanomedicine, Volume I:  Basic Capabilities, Landes Bioscience, Georgetown, TX, 1999, pp. 18-20;  http://www.nanomedicine.com/NMI/1.2.2.htm

 

31.  A.D. de Grey, B.N. Ames, J.K. Andersen, A. Bartke, J. Campisi, C.B. Heward, R.J. McCarter, G. Stock, “Time to talk SENS: critiquing the immutability of human aging,” Annals of the New York Academy of Sciences 959(April 2002):452-462, 463-465 (discussion);  A.D. de Grey, J.W. Baynes, D. Berd, C.B. Heward, G. Pawelec, G. Stock, “Is human aging still mysterious enough to be left only to scientists?” Bioessays 24(July 2002):667-676, Bioessays 25(January 2003):93-95 (discussion);  A.D. de Grey, “An engineer’s approach to the development of real anti-aging medicine,” Sci. Aging Knowledge Environ. 2003(8 January 2003):VP1;  A.D. de Grey, “Challenging but essential targets for genuine anti-aging drugs,” Expert Opinion Therapeutic Targets 7(February 2003):1-5.

 

32.  Richard A. Miller, “Extending life: scientific prospects and political obstacles,” Milbank Quarterly 80(March 2002):155-74;  A.D. de Grey, “The foreseeability of real anti-aging medicine: focusing the debate,” Experimental Gerontology. 38(September 2003):927-934.

 

33.  Robert A. Freitas Jr., “Section 2.4.1 Molecular Mechanical Components,” Nanomedicine, Volume I:  Basic Capabilities, Landes Bioscience, Georgetown, TX, 1999, pp. 61-64;  http://www.nanomedicine.com/NMI/2.4.1.htm

 

34.  T. Cagin, A. Jaramillo-Botero, G. Gao, W.A. Goddard III, “Molecular mechanics and molecular dynamics analysis of Drexler-Merkle gears and neon pump,” Nanotechnology 9(September 1998):143-152;  http://www.wag.caltech.edu/foresight/foresight_1.html

 

35.  K.E. Drexler, R.C. Merkle, “Simple pump selective for neon”, Institute for Molecular Manufacturing (IMM) website;  http://www.imm.org/Parts/Parts1.html or http://www.imm.org/Images/pumpApartC.jpg

 

36.  Ralph C. Merkle, Robert A. Freitas Jr., “Theoretical analysis of a carbon-carbon dimer placement tool for diamond mechanosynthesis,” Journal of Nanoscience and Nanotechnology 3(June 2003):319-324;  http://www.rfreitas.com/Nano/JNNDimerTool.pdf

 

37.  Jingping Peng, Robert A. Freitas Jr., Ralph C. Merkle, “Theoretical Analysis of Diamond Mechanosynthesis.  Part I.  Stability of C2 Mediated Growth of Nanocrystalline Diamond C(110) Surface,” Journal of Computational and Theoretical Nanoscience 1(March 2004);  David J. Mann, Jingping Peng, Robert A. Freitas Jr., Ralph C. Merkle, “Theoretical Analysis of Diamond Mechanosynthesis.  Part II.  C2 Mediated Growth of Diamond C(110) Surface via Si/Ge-Triadamantane Dimer Placement Tools,” Journal of Computational and Theoretical Nanoscience 1(March 2004).

 

38.  Robert A. Freitas Jr., Ralph C. Merkle, Diamond Surfaces and Diamond Mechanosynthesis, Landes Bioscience, Georgetown, TX, 2005.  In preparation.

 

39.  Ralph C. Merkle, Eric G. Parker, George D. Skidmore, “Method and system for self-replicating manufacturing stations,” United States Patent No. 6,510,359, 21 January 2003.

 

40.  Robert A. Freitas Jr., Ralph C. Merkle, Kinematic Self-Replicating Machines, Landes Bioscience, Georgetown, TX, 2004.  In press.

 

41.  Robert A. Freitas Jr., “Exploratory design in medical nanotechnology: A mechanical artificial red cell,” Artificial Cells, Blood Substitutes, and Immobilization Biotechnology 26(1998):411-430;  http://www.foresight.org/Nanomedicine/Respirocytes.html.  Images available at Nanomedicine Art Gallery, Foresight Institute website:  http://www.foresight.org/Nanomedicine/Gallery/Species/Respirocytes.html

 

42.  Lawrence Fields, Jillian Rose, “Animation of a respirocyte (an artificial red blood cell) being injected into the bloodstream,” PBS documentary “Beyond Human,” air date 15 May 2001, Phlesch Bubble Productions website;  http://www.phleschbubble.com/album/beyondhuman/respirocyte01.htm

 

43.  A brief summary description may be found at:  Robert A. Freitas Jr., “Microbivores: Artificial Mechanical Phagocytes,” Foresight Update, No. 44, 31 March 2001, pp. 11-13;  http://www.imm.org/Reports/Rep025.html.  The full technical paper is at:  Robert A. Freitas Jr., “Microbivores: Artificial Mechanical Phagocytes using Digest and Discharge Protocol,” Zyvex preprint, March 2001, Robert A . Freitas Jr. website;  http://www.rfreitas.com/Nano/Microbivores.htm.  Images available at Nanomedicine Art Gallery, Foresight Institute website:  http://www.foresight.org/Nanomedicine/Gallery/Species/Microbivores.html

 

44.  Robert A. Freitas Jr., “Section 15.4.2.3 Geometrical Trapping in Spleen Vasculature,” Nanomedicine, Volume IIA:  Biocompatibility, Landes Bioscience, Georgetown, TX, 2003, pp. 95-97;  http://www.nanomedicine.com/NMIIA/15.4.2.3.htm

 

45.  K. Eric Drexler, “Section 13.4.1  A bounded-continuum design for a stiff manipulator,” Nanosystems:  Molecular Machinery, Manufacturing, and Computation, John Wiley & Sons, New York, 1992, pp. 398-407.

 

46.  Robert A. Freitas Jr., “Chromallocytes:  Cell Repair Nanorobots for Chromosome Replacement Therapy,” 2004; in preparation.

 

47.  Robert A. Freitas Jr., Christopher J. Phoenix, “Vasculoid: A personal nanomedical appliance to replace human blood,” Journal of Evolution and Technology 11(April 2002);  http://www.jetpress.org/volume11/vasculoid.html

 

[All websites accessed 6 January 2004]